-
Rule 1 - Hierarchies | Jordan B. Peterson
The full lecture can be found here: https://www.youtube.com/watch?v=dPv1RYsi7sA
Please do not forget to subscribe to the channel so you can enjoy weekly videos.
We would like to thank all of you for the outpouring of kindness that Dr. Peterson has received after his Return Home video was released last week.
As we continue to develop our foreign language channels, we encourage you to view our Russian and Arabic links below.
Russian YouTube: https://bit.ly/3lSZcez
Russian Instagram: https://www.instagram.com/jordan.b.peterson_russia/
Arabic Facebook: https://www.facebook.com/JordanPetersonArabic/
Arabic Instagram: https://www.instagram.com/jordan.b.peterson_arabic/?hl=en
Other ways to connect with Dr. Peterson:
Join the JBP newsletter: https://mailchi.mp/jbpdaily/jbp-weekly-signup
Po...
published: 06 Nov 2020
-
Jordan Peterson - Why Hierarchies are Necessary
original source: https://youtu.be/6sUtOOOVcqw?t=6m28s
This interview is part of a Rebel Wisdom series 'What the left can learn from Jordan Peterson' which you can watch on https://youtu.be/6sUtOOOVcqw or visit the Rebel Wisdom channel: https://www.youtube.com/c/rebelwisdom
If you want to support Dr. Peterson's work,
you can make a donation on his website:
https://www.jordanbpeterson.com/donate
If you like his lectures, you will enjoy his recent book:
12 Rules for Life: An Antidote to Chaos: http://amzn.to/2yvJf9L
published: 03 Aug 2018
-
Understanding Hierarchy in Design
Learn how to build Custom designed websites with Webflow:
http://zpr.io/gVTUk
-
Flux is proudly sponsored by Webflow, start a new account with an awesome discount:
http://bit.ly/FluxWebflowDiscount
-
Instagram: https://www.instagram.com/ransegall/
Twitter: http://twitter.com/ransegall
-
Gear & Book Recommendations: http://bit.ly/2ohFOuj
published: 09 Aug 2019
-
11 Visual Hierarchy Design Principles - Learn How to Improve and Create Beautiful Graphic Designs
Want to spice up your designs? Learning all about visual hierarchy design principles can help you create beautiful graphics that create the perfect flow for your reader. Get started creating your own designs with Visme: https://www.visme.co/
---
This video takes you through the 11 visual hierarchy design principles to help you take your designs to the next level!
What makes a great design? Even amateurs and who consider themselves complete non-designers can create effective compositions by prioritizing their content. What is the most important element of your design? What do you want audiences to notice second or third?
Visual hierarchy is a method of organizing design elements in order of importance. In other words, it’s a set of principles that influence the order in which we notic...
published: 30 Jan 2019
-
Music to Realize Your Prophecy - Hierarchy
From my new album: Bloodline
Download or Stream: https://smarturl.it/x_Bloodline_x
Composer: Greg Dombrowski
https://www.instagram.com/thesecession/
Publisher: Secession Studios
https://www.secessionstudios.com/
Mixing & Mastering: Satoshi Noguchi
https://www.satoshinoguchi.com/
published: 01 Nov 2021
-
Herd Hierarchy: Colin ranks the top 10 teams in the NFL after Week 17 | NFL | THE HERD
Colin Cowherd's ten best teams in the NFL. Find out which squad he thinks is the best in the league after Week 17.
#TheHerd #NFL #Week17
Download the free-to-play FOX Bet Super 6 app: https://foxs.pt/3z96p0j
SUBSCRIBE to get all the latest content from The Herd: http://foxs.pt/SubscribeTHEHERD
The all-new FOX Sports App, built for the modern sports fan: https://tinyurl.com/y4uouolb
►Watch the latest content from The Herd: http://foxs.pt/LatestOnTheHerd
▶First Things First's YouTube channel: http://foxs.pt/SubscribeFIRSTTHINGSFIRST
►UNDISPUTED’s YouTube channel: http://foxs.pt/SubscribeUNDISPUTED
►Speak for Yourself’s YouTube channel: http://foxs.pt/SubscribeSPEAKFORYOURSELF
►FOX Bet Live’s YouTube Channel: https://foxs.pt/SubscribeFOXBETLIVE
►Club Shay Shay’s YouTube Channel: htt...
published: 04 Jan 2022
-
What is Hierarchy ? | What is meant by a hierarchical structure? | example of hierarchy Urdu - Hindi
In this video, i will tell you What is Hierarchy ? | What is meant by a hierarchical structure? | example of hierarchy Urdu - Hindi
My Website: https://www.socialnewstv.com/
My Facebook: https://www.facebook.com/Syedismaeelleo/?ref=bookmarks
My WhatsApp Group: https://chat.whatsapp.com/invite/3pFUU0ntyMi6zVMVvO4LII
Dear Students!
Here you will get all possible help and personal assistance and you can ask your doubts & queries through comments or you can join our Facebook Page.
For more lectures please visit my channel or click on below links:
Bonus Plans and Benefits | Urdu - Hindi
https://www.youtube.com/watch?v=uaSsdK6xgbw
The Basic Components of Employee Compensation and Benefits | Urdu - Hindi
https://www.youtube.com/watch?v=J4nY6oeH7aI
What is Employee Retention | Urdu Hindi
h...
published: 11 Jul 2019
-
Biblical Series III: God and the Hierarchy of Authority
Although I thought I might get to Genesis II in this third lecture, and begin talking about Adam & Eve, it didn't turn out that way. There was more to be said about the idea of God as creator (with the Word as the process underlying the act of creation). I didn't mind, because it is very important to get God and the Creation of the Universe right before moving on :) .
In this lecture, I tried to outline something like this: for anything to be, there has to be a substrate (call it a potential) from which it emerges, a structure that provides the possibility of imposing order on that substrate, and the act of ordering, itself. So the first is something like the precosmogonic chaos (implicitly feminine); the second, God the Father; the third, what the Christian West has portrayed as the So...
published: 06 Jun 2017
-
Jordan Peterson Explains the Male Dominance Hierarchy - The Joe Rogan Experience
Joe Rogan & Jordan Peterson discuss the male dominance hierarchy.
Taken from Joe Rogan Experience #958.
published: 10 May 2017
-
Why Maslow's Hierarchy Of Needs Matters
Maslow's Hierarchy, (or Pyramid), of Needs is one of the central ideas in modern economics and sociology. The work of a once little-known American psychologist, it has grown into an indispensable guide to understanding the modern world. This film explains who Maslow was, what his pyramid is, and why it matters so much.
Sign up to our new newsletter and get 10% off your first online order of a book, product or class: https://bit.ly/2LayJ9F
For gifts and more from The School of Life, visit our online shop: https://bit.ly/2WWC6Yg
Our website has classes, articles and products to help you think and grow: https://bit.ly/2Io7HxF
2VysjqM
FURTHER READING
You can read more on this and other subjects on our blog, here: https://bit.ly/2WQcz2G
“One of the most legendary ideas in the history of psyc...
published: 10 Apr 2019
10:20
Rule 1 - Hierarchies | Jordan B. Peterson
The full lecture can be found here: https://www.youtube.com/watch?v=dPv1RYsi7sA
Please do not forget to subscribe to the channel so you can enjoy weekly videos...
The full lecture can be found here: https://www.youtube.com/watch?v=dPv1RYsi7sA
Please do not forget to subscribe to the channel so you can enjoy weekly videos.
We would like to thank all of you for the outpouring of kindness that Dr. Peterson has received after his Return Home video was released last week.
As we continue to develop our foreign language channels, we encourage you to view our Russian and Arabic links below.
Russian YouTube: https://bit.ly/3lSZcez
Russian Instagram: https://www.instagram.com/jordan.b.peterson_russia/
Arabic Facebook: https://www.facebook.com/JordanPetersonArabic/
Arabic Instagram: https://www.instagram.com/jordan.b.peterson_arabic/?hl=en
Other ways to connect with Dr. Peterson:
Join the JBP newsletter: https://mailchi.mp/jbpdaily/jbp-weekly-signup
Podcast: https://jordanbpeterson.com/podcast/
Instagram: https://www.instagram.com/jordan.b.peterson/
Facebook: https://www.facebook.com/drjordanpeterson/
Direct Support: https://www.jordanbpeterson.com/donate/
https://wn.com/Rule_1_Hierarchies_|_Jordan_B._Peterson
The full lecture can be found here: https://www.youtube.com/watch?v=dPv1RYsi7sA
Please do not forget to subscribe to the channel so you can enjoy weekly videos.
We would like to thank all of you for the outpouring of kindness that Dr. Peterson has received after his Return Home video was released last week.
As we continue to develop our foreign language channels, we encourage you to view our Russian and Arabic links below.
Russian YouTube: https://bit.ly/3lSZcez
Russian Instagram: https://www.instagram.com/jordan.b.peterson_russia/
Arabic Facebook: https://www.facebook.com/JordanPetersonArabic/
Arabic Instagram: https://www.instagram.com/jordan.b.peterson_arabic/?hl=en
Other ways to connect with Dr. Peterson:
Join the JBP newsletter: https://mailchi.mp/jbpdaily/jbp-weekly-signup
Podcast: https://jordanbpeterson.com/podcast/
Instagram: https://www.instagram.com/jordan.b.peterson/
Facebook: https://www.facebook.com/drjordanpeterson/
Direct Support: https://www.jordanbpeterson.com/donate/
- published: 06 Nov 2020
- views: 79430
4:50
Jordan Peterson - Why Hierarchies are Necessary
original source: https://youtu.be/6sUtOOOVcqw?t=6m28s
This interview is part of a Rebel Wisdom series 'What the left can learn from Jordan Peterson' which you c...
original source: https://youtu.be/6sUtOOOVcqw?t=6m28s
This interview is part of a Rebel Wisdom series 'What the left can learn from Jordan Peterson' which you can watch on https://youtu.be/6sUtOOOVcqw or visit the Rebel Wisdom channel: https://www.youtube.com/c/rebelwisdom
If you want to support Dr. Peterson's work,
you can make a donation on his website:
https://www.jordanbpeterson.com/donate
If you like his lectures, you will enjoy his recent book:
12 Rules for Life: An Antidote to Chaos: http://amzn.to/2yvJf9L
https://wn.com/Jordan_Peterson_Why_Hierarchies_Are_Necessary
original source: https://youtu.be/6sUtOOOVcqw?t=6m28s
This interview is part of a Rebel Wisdom series 'What the left can learn from Jordan Peterson' which you can watch on https://youtu.be/6sUtOOOVcqw or visit the Rebel Wisdom channel: https://www.youtube.com/c/rebelwisdom
If you want to support Dr. Peterson's work,
you can make a donation on his website:
https://www.jordanbpeterson.com/donate
If you like his lectures, you will enjoy his recent book:
12 Rules for Life: An Antidote to Chaos: http://amzn.to/2yvJf9L
- published: 03 Aug 2018
- views: 98715
9:31
Understanding Hierarchy in Design
Learn how to build Custom designed websites with Webflow:
http://zpr.io/gVTUk
-
Flux is proudly sponsored by Webflow, start a new account with an awesome discou...
Learn how to build Custom designed websites with Webflow:
http://zpr.io/gVTUk
-
Flux is proudly sponsored by Webflow, start a new account with an awesome discount:
http://bit.ly/FluxWebflowDiscount
-
Instagram: https://www.instagram.com/ransegall/
Twitter: http://twitter.com/ransegall
-
Gear & Book Recommendations: http://bit.ly/2ohFOuj
https://wn.com/Understanding_Hierarchy_In_Design
Learn how to build Custom designed websites with Webflow:
http://zpr.io/gVTUk
-
Flux is proudly sponsored by Webflow, start a new account with an awesome discount:
http://bit.ly/FluxWebflowDiscount
-
Instagram: https://www.instagram.com/ransegall/
Twitter: http://twitter.com/ransegall
-
Gear & Book Recommendations: http://bit.ly/2ohFOuj
- published: 09 Aug 2019
- views: 37571
8:28
11 Visual Hierarchy Design Principles - Learn How to Improve and Create Beautiful Graphic Designs
Want to spice up your designs? Learning all about visual hierarchy design principles can help you create beautiful graphics that create the perfect flow for you...
Want to spice up your designs? Learning all about visual hierarchy design principles can help you create beautiful graphics that create the perfect flow for your reader. Get started creating your own designs with Visme: https://www.visme.co/
---
This video takes you through the 11 visual hierarchy design principles to help you take your designs to the next level!
What makes a great design? Even amateurs and who consider themselves complete non-designers can create effective compositions by prioritizing their content. What is the most important element of your design? What do you want audiences to notice second or third?
Visual hierarchy is a method of organizing design elements in order of importance. In other words, it’s a set of principles that influence the order in which we notice what we see.
Utilizing certain hierarchy principles can help even non-designers create successful visual presentations that are both efficient and effective.
While the precise number of hierarchy principles varies greatly depending on the source, we’ve divided them into the following concepts:
-Size and Scale
- Perspective
- Color and Contrast
- Typography
- Proximity
- Use of Negative Space
- Alignment
- Rules of Odds
- Using Repetition
- Leading with Lines
- Rule of Thirds
These golden rules help us compose designs that are aesthetically pleasing and attract the right attention and can be followed by anyone without design experience to help you take your boring Powerpoints, Reports, Graphics, and pretty much any type of visual to a whole new level that you can be proud of.
Watch the video, and if you want to learn more about each principle, be sure to visit our our blog: https://blog.visme.co/visual-hierarchy/
https://wn.com/11_Visual_Hierarchy_Design_Principles_Learn_How_To_Improve_And_Create_Beautiful_Graphic_Designs
Want to spice up your designs? Learning all about visual hierarchy design principles can help you create beautiful graphics that create the perfect flow for your reader. Get started creating your own designs with Visme: https://www.visme.co/
---
This video takes you through the 11 visual hierarchy design principles to help you take your designs to the next level!
What makes a great design? Even amateurs and who consider themselves complete non-designers can create effective compositions by prioritizing their content. What is the most important element of your design? What do you want audiences to notice second or third?
Visual hierarchy is a method of organizing design elements in order of importance. In other words, it’s a set of principles that influence the order in which we notice what we see.
Utilizing certain hierarchy principles can help even non-designers create successful visual presentations that are both efficient and effective.
While the precise number of hierarchy principles varies greatly depending on the source, we’ve divided them into the following concepts:
-Size and Scale
- Perspective
- Color and Contrast
- Typography
- Proximity
- Use of Negative Space
- Alignment
- Rules of Odds
- Using Repetition
- Leading with Lines
- Rule of Thirds
These golden rules help us compose designs that are aesthetically pleasing and attract the right attention and can be followed by anyone without design experience to help you take your boring Powerpoints, Reports, Graphics, and pretty much any type of visual to a whole new level that you can be proud of.
Watch the video, and if you want to learn more about each principle, be sure to visit our our blog: https://blog.visme.co/visual-hierarchy/
- published: 30 Jan 2019
- views: 124800
6:17
Music to Realize Your Prophecy - Hierarchy
From my new album: Bloodline
Download or Stream: https://smarturl.it/x_Bloodline_x
Composer: Greg Dombrowski
https://www.instagram.com/thesecession/
Publishe...
From my new album: Bloodline
Download or Stream: https://smarturl.it/x_Bloodline_x
Composer: Greg Dombrowski
https://www.instagram.com/thesecession/
Publisher: Secession Studios
https://www.secessionstudios.com/
Mixing & Mastering: Satoshi Noguchi
https://www.satoshinoguchi.com/
https://wn.com/Music_To_Realize_Your_Prophecy_Hierarchy
From my new album: Bloodline
Download or Stream: https://smarturl.it/x_Bloodline_x
Composer: Greg Dombrowski
https://www.instagram.com/thesecession/
Publisher: Secession Studios
https://www.secessionstudios.com/
Mixing & Mastering: Satoshi Noguchi
https://www.satoshinoguchi.com/
- published: 01 Nov 2021
- views: 145744
8:11
Herd Hierarchy: Colin ranks the top 10 teams in the NFL after Week 17 | NFL | THE HERD
Colin Cowherd's ten best teams in the NFL. Find out which squad he thinks is the best in the league after Week 17.
#TheHerd #NFL #Week17
Download the free-to-...
Colin Cowherd's ten best teams in the NFL. Find out which squad he thinks is the best in the league after Week 17.
#TheHerd #NFL #Week17
Download the free-to-play FOX Bet Super 6 app: https://foxs.pt/3z96p0j
SUBSCRIBE to get all the latest content from The Herd: http://foxs.pt/SubscribeTHEHERD
The all-new FOX Sports App, built for the modern sports fan: https://tinyurl.com/y4uouolb
►Watch the latest content from The Herd: http://foxs.pt/LatestOnTheHerd
▶First Things First's YouTube channel: http://foxs.pt/SubscribeFIRSTTHINGSFIRST
►UNDISPUTED’s YouTube channel: http://foxs.pt/SubscribeUNDISPUTED
►Speak for Yourself’s YouTube channel: http://foxs.pt/SubscribeSPEAKFORYOURSELF
►FOX Bet Live’s YouTube Channel: https://foxs.pt/SubscribeFOXBETLIVE
►Club Shay Shay’s YouTube Channel: http://foxs.pt/SubscribeCLUBSHAYSHAY
▶Titus & Tate's YouTube channel: http://foxs.pt/SubscribeTITUSANDTATE
See more from THE HERD: http://foxs.pt/THEHERDFoxSports
Like THE HERD on Facebook: http://foxs.pt/THEHERDFacebook
Follow THE HERD on Twitter: http://foxs.pt/THEHERDTwitter
Follow THE HERD on Instagram: http://foxs.pt/THEHERDInstagram
Follow Colin Cowherd on Twitter: http://foxs.pt/ColinCowherdTwitter
About The Herd with Colin Cowherd:
The Herd with Colin Cowherd is a three-hour sports television and radio show on FS1 and iHeartRadio. Every day, Colin will give you his authentic, unfiltered opinion on the day’s biggest sports topics.
Herd Hierarchy: Colin ranks the top 10 teams in the NFL after Week 17 | NFL | THE HERD
https://youtu.be/Evy3xZXqoKs
The Herd with Colin Cowherd
https://www.youtube.com/c/colincowherd
https://wn.com/Herd_Hierarchy_Colin_Ranks_The_Top_10_Teams_In_The_Nfl_After_Week_17_|_Nfl_|_The_Herd
Colin Cowherd's ten best teams in the NFL. Find out which squad he thinks is the best in the league after Week 17.
#TheHerd #NFL #Week17
Download the free-to-play FOX Bet Super 6 app: https://foxs.pt/3z96p0j
SUBSCRIBE to get all the latest content from The Herd: http://foxs.pt/SubscribeTHEHERD
The all-new FOX Sports App, built for the modern sports fan: https://tinyurl.com/y4uouolb
►Watch the latest content from The Herd: http://foxs.pt/LatestOnTheHerd
▶First Things First's YouTube channel: http://foxs.pt/SubscribeFIRSTTHINGSFIRST
►UNDISPUTED’s YouTube channel: http://foxs.pt/SubscribeUNDISPUTED
►Speak for Yourself’s YouTube channel: http://foxs.pt/SubscribeSPEAKFORYOURSELF
►FOX Bet Live’s YouTube Channel: https://foxs.pt/SubscribeFOXBETLIVE
►Club Shay Shay’s YouTube Channel: http://foxs.pt/SubscribeCLUBSHAYSHAY
▶Titus & Tate's YouTube channel: http://foxs.pt/SubscribeTITUSANDTATE
See more from THE HERD: http://foxs.pt/THEHERDFoxSports
Like THE HERD on Facebook: http://foxs.pt/THEHERDFacebook
Follow THE HERD on Twitter: http://foxs.pt/THEHERDTwitter
Follow THE HERD on Instagram: http://foxs.pt/THEHERDInstagram
Follow Colin Cowherd on Twitter: http://foxs.pt/ColinCowherdTwitter
About The Herd with Colin Cowherd:
The Herd with Colin Cowherd is a three-hour sports television and radio show on FS1 and iHeartRadio. Every day, Colin will give you his authentic, unfiltered opinion on the day’s biggest sports topics.
Herd Hierarchy: Colin ranks the top 10 teams in the NFL after Week 17 | NFL | THE HERD
https://youtu.be/Evy3xZXqoKs
The Herd with Colin Cowherd
https://www.youtube.com/c/colincowherd
- published: 04 Jan 2022
- views: 171523
9:41
What is Hierarchy ? | What is meant by a hierarchical structure? | example of hierarchy Urdu - Hindi
In this video, i will tell you What is Hierarchy ? | What is meant by a hierarchical structure? | example of hierarchy Urdu - Hindi
My Website: https://www.soc...
In this video, i will tell you What is Hierarchy ? | What is meant by a hierarchical structure? | example of hierarchy Urdu - Hindi
My Website: https://www.socialnewstv.com/
My Facebook: https://www.facebook.com/Syedismaeelleo/?ref=bookmarks
My WhatsApp Group: https://chat.whatsapp.com/invite/3pFUU0ntyMi6zVMVvO4LII
Dear Students!
Here you will get all possible help and personal assistance and you can ask your doubts & queries through comments or you can join our Facebook Page.
For more lectures please visit my channel or click on below links:
Bonus Plans and Benefits | Urdu - Hindi
https://www.youtube.com/watch?v=uaSsdK6xgbw
The Basic Components of Employee Compensation and Benefits | Urdu - Hindi
https://www.youtube.com/watch?v=J4nY6oeH7aI
What is Employee Retention | Urdu Hindi
https://www.youtube.com/watch?v=wqUe2tM4piQ
What is Inventory Management in English | Basic Concept
https://www.youtube.com/watch?v=L002PtIq8Dc
What is Compensation | Concept of Compensation | Meaning of Compensation Hindi & Urdu: https://www.youtube.com/watch?v=qr8qWh6iTXs&t;=255s
Study of Comparative Public Administration | Hindi & Urdu
https://www.youtube.com/watch?v=ygM3CeCwlX0&t;=9s
The basic concept of Human Resources Management for the new student in Urdu & Hindi
https://www.youtube.com/watch?v=OFa9iCF2lbM&t;=155s
What is public policy?
https://www.youtube.com/watch?v=rF41G4763i4
What is Convention & law?
https://www.youtube.com/watch?v=7LWHegrDCls&t;=34s
What is the equity theory?
https://www.youtube.com/watch?v=3WRzgv4ZaOM&t;=120s
What is Communication Process in Simple words Urdu - Hindi
https://www.youtube.com/watch?v=pB-M_svhWnE
Function & Categories of Communication | Verbal | Nonverbal | Written in Urdu - Hindi
https://www.youtube.com/watch?v=sHvvm2XxG2M
What is Communication? | Purpose & Meaning of Communication Urdu - Hindi
https://www.youtube.com/watch?v=GMQUg7DYfpc
Difference between Public Policy and Public Administration Urdu Hindi
https://www.youtube.com/watch?v=F5IibjoxJ8Q
https://wn.com/What_Is_Hierarchy_|_What_Is_Meant_By_A_Hierarchical_Structure_|_Example_Of_Hierarchy_Urdu_Hindi
In this video, i will tell you What is Hierarchy ? | What is meant by a hierarchical structure? | example of hierarchy Urdu - Hindi
My Website: https://www.socialnewstv.com/
My Facebook: https://www.facebook.com/Syedismaeelleo/?ref=bookmarks
My WhatsApp Group: https://chat.whatsapp.com/invite/3pFUU0ntyMi6zVMVvO4LII
Dear Students!
Here you will get all possible help and personal assistance and you can ask your doubts & queries through comments or you can join our Facebook Page.
For more lectures please visit my channel or click on below links:
Bonus Plans and Benefits | Urdu - Hindi
https://www.youtube.com/watch?v=uaSsdK6xgbw
The Basic Components of Employee Compensation and Benefits | Urdu - Hindi
https://www.youtube.com/watch?v=J4nY6oeH7aI
What is Employee Retention | Urdu Hindi
https://www.youtube.com/watch?v=wqUe2tM4piQ
What is Inventory Management in English | Basic Concept
https://www.youtube.com/watch?v=L002PtIq8Dc
What is Compensation | Concept of Compensation | Meaning of Compensation Hindi & Urdu: https://www.youtube.com/watch?v=qr8qWh6iTXs&t;=255s
Study of Comparative Public Administration | Hindi & Urdu
https://www.youtube.com/watch?v=ygM3CeCwlX0&t;=9s
The basic concept of Human Resources Management for the new student in Urdu & Hindi
https://www.youtube.com/watch?v=OFa9iCF2lbM&t;=155s
What is public policy?
https://www.youtube.com/watch?v=rF41G4763i4
What is Convention & law?
https://www.youtube.com/watch?v=7LWHegrDCls&t;=34s
What is the equity theory?
https://www.youtube.com/watch?v=3WRzgv4ZaOM&t;=120s
What is Communication Process in Simple words Urdu - Hindi
https://www.youtube.com/watch?v=pB-M_svhWnE
Function & Categories of Communication | Verbal | Nonverbal | Written in Urdu - Hindi
https://www.youtube.com/watch?v=sHvvm2XxG2M
What is Communication? | Purpose & Meaning of Communication Urdu - Hindi
https://www.youtube.com/watch?v=GMQUg7DYfpc
Difference between Public Policy and Public Administration Urdu Hindi
https://www.youtube.com/watch?v=F5IibjoxJ8Q
- published: 11 Jul 2019
- views: 22583
2:40:53
Biblical Series III: God and the Hierarchy of Authority
Although I thought I might get to Genesis II in this third lecture, and begin talking about Adam & Eve, it didn't turn out that way. There was more to be said a...
Although I thought I might get to Genesis II in this third lecture, and begin talking about Adam & Eve, it didn't turn out that way. There was more to be said about the idea of God as creator (with the Word as the process underlying the act of creation). I didn't mind, because it is very important to get God and the Creation of the Universe right before moving on :) .
In this lecture, I tried to outline something like this: for anything to be, there has to be a substrate (call it a potential) from which it emerges, a structure that provides the possibility of imposing order on that substrate, and the act of ordering, itself. So the first is something like the precosmogonic chaos (implicitly feminine); the second, God the Father; the third, what the Christian West has portrayed as the Son (the Word of Truth).
Producer Credit and thanks to the following $200/month Patreon supporters. Without such support, this series would not have happened: Adam Clarke, Alexander Meckhai’el Beraeros, Andy Baker, Arden C. Armstrong, Badr Amari, BC, Ben Baker, Benjamin Cracknell, Brandon Yates, Chad Grills, Chris Martakis, Christopher Ballew, Craig Morrison, Daljeet Singh, Damian Fink, Dan Gaylinn, Daren Connel, David Johnson, David Tien, Donald Mitchell, Eleftheria Libertatem, Enrico Lejaru, George Diaz, GeorgeB, Holly Lindquist, Ian Trick, James Bradley, James N. Daniel, III, Jan Schanek, Jason R. Ferenc, Jesse Michalak, Joe Cairns, Joel Kurth, John Woolley, Johnny Vinje, Julie Byrne, Keith Jones, Kevin Fallon, Kevin Patrick McSurdy, Kevin Van Eekeren, Kristina Ripka, Louise Parberry, Matt Karamazov, Matt Sattler, Mayor Berkowitz , Michael Thiele, Nathan Claus, Nick Swenson , Patricia Newman, Robb Kelley, Robin Otto, Ryan Kane, Sabish Balan, Salman Alsabah, Scott Carter, Sean C., Sean Magin, Sebastian Thaci, Shiqi Hu, Soheil Daftarian, Srdan Pavlovic, Starting Ideas, Too Analytical, Trey McLemore, William Wilkinson, Yazz Troche, Zachary Vader
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https://wn.com/Biblical_Series_Iii_God_And_The_Hierarchy_Of_Authority
Although I thought I might get to Genesis II in this third lecture, and begin talking about Adam & Eve, it didn't turn out that way. There was more to be said about the idea of God as creator (with the Word as the process underlying the act of creation). I didn't mind, because it is very important to get God and the Creation of the Universe right before moving on :) .
In this lecture, I tried to outline something like this: for anything to be, there has to be a substrate (call it a potential) from which it emerges, a structure that provides the possibility of imposing order on that substrate, and the act of ordering, itself. So the first is something like the precosmogonic chaos (implicitly feminine); the second, God the Father; the third, what the Christian West has portrayed as the Son (the Word of Truth).
Producer Credit and thanks to the following $200/month Patreon supporters. Without such support, this series would not have happened: Adam Clarke, Alexander Meckhai’el Beraeros, Andy Baker, Arden C. Armstrong, Badr Amari, BC, Ben Baker, Benjamin Cracknell, Brandon Yates, Chad Grills, Chris Martakis, Christopher Ballew, Craig Morrison, Daljeet Singh, Damian Fink, Dan Gaylinn, Daren Connel, David Johnson, David Tien, Donald Mitchell, Eleftheria Libertatem, Enrico Lejaru, George Diaz, GeorgeB, Holly Lindquist, Ian Trick, James Bradley, James N. Daniel, III, Jan Schanek, Jason R. Ferenc, Jesse Michalak, Joe Cairns, Joel Kurth, John Woolley, Johnny Vinje, Julie Byrne, Keith Jones, Kevin Fallon, Kevin Patrick McSurdy, Kevin Van Eekeren, Kristina Ripka, Louise Parberry, Matt Karamazov, Matt Sattler, Mayor Berkowitz , Michael Thiele, Nathan Claus, Nick Swenson , Patricia Newman, Robb Kelley, Robin Otto, Ryan Kane, Sabish Balan, Salman Alsabah, Scott Carter, Sean C., Sean Magin, Sebastian Thaci, Shiqi Hu, Soheil Daftarian, Srdan Pavlovic, Starting Ideas, Too Analytical, Trey McLemore, William Wilkinson, Yazz Troche, Zachary Vader
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- published: 06 Jun 2017
- views: 2517513
11:30
Jordan Peterson Explains the Male Dominance Hierarchy - The Joe Rogan Experience
Joe Rogan & Jordan Peterson discuss the male dominance hierarchy.
Taken from Joe Rogan Experience #958.
Joe Rogan & Jordan Peterson discuss the male dominance hierarchy.
Taken from Joe Rogan Experience #958.
https://wn.com/Jordan_Peterson_Explains_The_Male_Dominance_Hierarchy_The_Joe_Rogan_Experience
Joe Rogan & Jordan Peterson discuss the male dominance hierarchy.
Taken from Joe Rogan Experience #958.
- published: 10 May 2017
- views: 598068
6:29
Why Maslow's Hierarchy Of Needs Matters
Maslow's Hierarchy, (or Pyramid), of Needs is one of the central ideas in modern economics and sociology. The work of a once little-known American psychologist,...
Maslow's Hierarchy, (or Pyramid), of Needs is one of the central ideas in modern economics and sociology. The work of a once little-known American psychologist, it has grown into an indispensable guide to understanding the modern world. This film explains who Maslow was, what his pyramid is, and why it matters so much.
Sign up to our new newsletter and get 10% off your first online order of a book, product or class: https://bit.ly/2LayJ9F
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2VysjqM
FURTHER READING
You can read more on this and other subjects on our blog, here: https://bit.ly/2WQcz2G
“One of the most legendary ideas in the history of psychology is located in an unassuming triangle divided into five sections referred to universally simply as ‘Maslow’s Pyramid of Needs’.
This profoundly influential pyramid first saw the world in an academic journal in the United States in 1943, where it was crudely drawn in black and white and surrounded by dense and jargon-rich text. It has since become a mainstay of psychological analyses, business presentations and online lectures – and grown ever more colourful and emphatic in the process…”
MORE SCHOOL OF LIFE
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Watch more films on Work and Capitalism in our playlist:
http://bit.ly/TSOLcapitalism
You can submit translations and transcripts on all of our videos here: https://www.youtube.com/timedtext_cs_panel?c=UC7IcJI8PUf5Z3zKxnZvTBog&tab;=2
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CREDITS
Produced in collaboration with:
Mike Booth
https://www.youtube.com/somegreybloke
Title animation produced in collaboration with
Vale Productions
https://www.valeproductions.co.uk/
https://wn.com/Why_Maslow's_Hierarchy_Of_Needs_Matters
Maslow's Hierarchy, (or Pyramid), of Needs is one of the central ideas in modern economics and sociology. The work of a once little-known American psychologist, it has grown into an indispensable guide to understanding the modern world. This film explains who Maslow was, what his pyramid is, and why it matters so much.
Sign up to our new newsletter and get 10% off your first online order of a book, product or class: https://bit.ly/2LayJ9F
For gifts and more from The School of Life, visit our online shop: https://bit.ly/2WWC6Yg
Our website has classes, articles and products to help you think and grow: https://bit.ly/2Io7HxF
2VysjqM
FURTHER READING
You can read more on this and other subjects on our blog, here: https://bit.ly/2WQcz2G
“One of the most legendary ideas in the history of psychology is located in an unassuming triangle divided into five sections referred to universally simply as ‘Maslow’s Pyramid of Needs’.
This profoundly influential pyramid first saw the world in an academic journal in the United States in 1943, where it was crudely drawn in black and white and surrounded by dense and jargon-rich text. It has since become a mainstay of psychological analyses, business presentations and online lectures – and grown ever more colourful and emphatic in the process…”
MORE SCHOOL OF LIFE
Visit us in person at our London HQ: https://bit.ly/2UoJAGt
Watch more films on Work and Capitalism in our playlist:
http://bit.ly/TSOLcapitalism
You can submit translations and transcripts on all of our videos here: https://www.youtube.com/timedtext_cs_panel?c=UC7IcJI8PUf5Z3zKxnZvTBog&tab;=2
Find out how more here: https://support.google.com/youtube/answer/6054623?hl=en-GB
SOCIAL MEDIA
Feel free to follow us at the links below:
2VysjqM
Facebook: https://www.facebook.com/theschooloflifelondon/
Twitter: https://twitter.com/TheSchoolOfLife
Instagram: https://www.instagram.com/theschooloflifelondon/
CREDITS
Produced in collaboration with:
Mike Booth
https://www.youtube.com/somegreybloke
Title animation produced in collaboration with
Vale Productions
https://www.valeproductions.co.uk/
- published: 10 Apr 2019
- views: 1818251
-
Deep Learning In 5 Minutes | What Is Deep Learning? | Deep Learning Explained Simply | Simplilearn
🔥 Enroll for FREE Artificial Intelligence Course & Get your Completion Certificate: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=Skillup-DeepLearning&utm;_medium=DescriptionFirstFold&utm;_source=youtube
This video on "What is Deep Learning" provides a fun and simple introduction to its concepts. We learn about where Deep Learning is implemented and move on to how it is different from machine learning and artificial intelligence. We will also look at what neural networks are and how they are trained to recognize digits written by hand. We further look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.
Start learning today's most in-demand skills for FREE. Visit us at https://www.simplilearn.com/skillup-free-...
published: 03 Jun 2019
-
But what is a neural network? | Chapter 1, Deep learning
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
Additional funding for this project provided by Amplify Partners
Typo correction: At 14 minutes 45 seconds, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, i...
published: 05 Oct 2017
-
Deep Learning Crash Course for Beginners
Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute beginners with no experience in programming. You will learn the key ideas behind deep learning without any code.
You'll learn about Neural Networks, Machine Learning constructs like Supervised, Unsupervised and Reinforcement Learning, the various types of Neural Network architectures, and more.
✏️ Course developed by Jason Dsouza. Check out his YouTube channel: http://youtube.com/jasmcaus
⭐️ Course Contents ⭐️
⌨️ (0:00) Introduction
⌨️ (1:18) What is Deep Learning
⌨️ (5:25) Introduction to Neural Networks
⌨️ (6:12) How do Neural Networks LEARN?
⌨️ (12:06) Core terminologies used in Deep Learning
⌨️ (12:11) Activation Functions
⌨️ (22:36) Loss Functions
...
published: 30 Jul 2020
-
Cancer Detection Using Deep Learning | Deep Learning Projects | Edureka | DL Rewind - 4
🔥Edureka Deep Learning With TensorFlow (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎): https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka video on 𝐂𝐚𝐧𝐜𝐞𝐫 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐔𝐬𝐢𝐧𝐠 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, will help you understand how to develop models using Convolution Neural Networks. We will also have a discussion on improving model accuracy using pretrained models.
🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s
🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV
📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.in...
published: 05 Nov 2021
-
Deep Learning Full Course - Learn Deep Learning in 6 Hours | Deep Learning Tutorial | Edureka
** AI & Deep Learning with TensorFlow (Use Code: YOUTUBE20): https://www.edureka.co/ai-deep-learning-with-tensorflow **
This Edureka Deep Learning Full Course video will help you understand and learn Deep Learning & Tensorflow in detail. This Deep Learning Tutorial is ideal for both beginners as well as professionals who want to master Deep Learning Algorithms. Below are the topics covered in this Deep Learning tutorial video:
00:00 Introduction
3:11 What is Deep Learning
3:55 Why Artificial Intelligence?
5:48 What is AI?
6:53 Applications of AI
8:43 Machine Learning
10:28 Types of Machine Learning
10:33 Supervised Learning
11:43 Unsupervised Learning
13:08 Reinforcement Learning
14:38 Limitations of Machine Learning
16:08 Deep Learning to the Rescue
19:28 What is Deep Learning?
22:58 Deep...
published: 08 Sep 2019
-
Deep Learning Basics: Introduction and Overview
An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks have inspired and energized an entire new generation of researchers. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.
INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/deep-learning-basics-slides
Playlist: http://bit.ly/deep-learning-playlist
Blog post: https://link.medium.com/TkE476jw2T
OUTLINE:
0:00 - Introduction
0:53 - Deep learning in one slide
4:55 - History of ideas and tools
9:43 - Simple example i...
published: 11 Jan 2019
-
MIT Introduction to Deep Learning | 6.S191
MIT Introduction to Deep Learning 6.S191: Lecture 1
*New 2021 Edition*
Foundations of Deep Learning
Lecturer: Alexander Amini
For all lectures, slides, and lab materials: http://introtodeeplearning.com/
Lecture Outline
0:00 - Introduction
4:48 - Course information
10:18 - Why deep learning?
12:28 - The perceptron
14:42 - Activation functions
17:48 - Perceptron example
21:43 - From perceptrons to neural networks
27:42 - Applying neural networks
30:21 - Loss functions
33:23 - Training and gradient descent
38:05 - Backpropagation
43:06 - Setting the learning rate
47:17 - Batched gradient descent
49:49 - Regularization: dropout and early stopping
55:55 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us on @MITDeepLearning on Twitter ...
published: 05 Feb 2021
-
Gradient descent, how neural networks learn | Chapter 2, Deep learning
Enjoy these videos? Consider sharing one or two.
Help fund future projects: https://www.patreon.com/3blue1brown
Special thanks to these supporters: http://3b1b.co/nn2-thanks
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
This video was supported by Amplify Partners.
For any early-stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com
To learn more, I highly recommend the book by Michael Nielsen
http://neuralnetworksanddeeplearning.com/
The book walks through the code behind the example in these videos, which you can find here:
https://github.com/mnielsen/neural-networks-and-deep-learning
MNIST database:
http://yann.lecun.com/exdb/mnist/
Also check out Chris Olah's blog:
http://colah.git...
published: 16 Oct 2017
-
Introduction to Deep Learning: Machine Learning vs. Deep Learning
Learn about the differences between deep learning and machine learning in this MATLAB® Tech Talk.
- MATLAB for Deep Learning: http://bit.ly/2Dl0jm4
Walk through several examples, and learn how to decide which method to use.
Learn more about Deep Learning: https://goo.gl/F8tBZi
Download a trial: https://goo.gl/PSa78r
The video outlines the specific workflow for solving a machine learning problem.
The video also outlines the differing requirements for machine learning and deep learning. You’ll learn about the key questions to ask before deciding between machine learning and deep learning.
The choice between machine learning or deep learning depends on your data and the problem you’re trying to solve. MATLAB can help you with both of these techniques – either separately or as a combined ...
published: 04 Apr 2017
-
Neural Network Architectures & Deep Learning
This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders.
Book website: http://databookuw.com/
Steve Brunton's website: eigensteve.com
Follow updates on Twitter @eigensteve
This video is part of a playlist "Intro to Data Science":
https://www.youtube.com/playlist?list=PLMrJAkhIeNNQV7wi9r7Kut8liLFMWQOXn
published: 06 Jun 2019
5:52
Deep Learning In 5 Minutes | What Is Deep Learning? | Deep Learning Explained Simply | Simplilearn
🔥 Enroll for FREE Artificial Intelligence Course & Get your Completion Certificate: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=Skillup-D...
🔥 Enroll for FREE Artificial Intelligence Course & Get your Completion Certificate: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=Skillup-DeepLearning&utm;_medium=DescriptionFirstFold&utm;_source=youtube
This video on "What is Deep Learning" provides a fun and simple introduction to its concepts. We learn about where Deep Learning is implemented and move on to how it is different from machine learning and artificial intelligence. We will also look at what neural networks are and how they are trained to recognize digits written by hand. We further look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.
Start learning today's most in-demand skills for FREE. Visit us at https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=AI&utm;_medium=Description&utm;_source=youtube
Choose over 300 in-demand skills and get access to 1000+ hours of video content for FREE in various technologies like Data Science, Cybersecurity, Project Management & Leadership, Digital Marketing, and much more.
Don't forget to take the quiz at 04:26!
To learn more about Deep Learning, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1
Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list;=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip
#DeepLearning #WhatIsDeepLearning #DeepLearningTutorial #DeepLearningCourse #DeepLearningExplained #Simplilearn
Simplilearn’s Deep Learning course will transform you into an expert in Deep Learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our Deep Learning course, you'll master Deep Learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as Deep Learning scientist.
Why Deep Learning?
It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial neural networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in Deep Learning models, learn to operate TensorFlow to manage neural networks and interpret the results. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.
You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement Deep Learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
4. Build Deep Learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial neural networks
6. Troubleshoot and improve Deep Learning models
7. Build your own Deep Learning project
8. Differentiate between machine learning, Deep Learning and artificial intelligence
There is booming demand for skilled Deep Learning engineers across a wide range of industries, making this Deep Learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this Deep Learning online course particularly for the following professionals:
1. Software engineers
2. Data scientists
3. Data analysts
4. Statisticians with an interest in Deep Learning
Learn more at: https://www.simplilearn.com/deep-learning-course-with-tensorflow-training?utm_campaign=DeepLearning&utm;_medium=Description&utm;_source=youtube
For more information about Simplilearn’s courses, visit:
- Facebook: https://www.facebook.com/Simplilearn
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- Website: https://www.simplilearn.com
Get the Android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0
https://wn.com/Deep_Learning_In_5_Minutes_|_What_Is_Deep_Learning_|_Deep_Learning_Explained_Simply_|_Simplilearn
🔥 Enroll for FREE Artificial Intelligence Course & Get your Completion Certificate: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=Skillup-DeepLearning&utm;_medium=DescriptionFirstFold&utm;_source=youtube
This video on "What is Deep Learning" provides a fun and simple introduction to its concepts. We learn about where Deep Learning is implemented and move on to how it is different from machine learning and artificial intelligence. We will also look at what neural networks are and how they are trained to recognize digits written by hand. We further look at some popular applications of Deep Learning. So, let’s dive into the world of Deep Learning with this video.
Start learning today's most in-demand skills for FREE. Visit us at https://www.simplilearn.com/skillup-free-online-courses?utm_campaign=AI&utm;_medium=Description&utm;_source=youtube
Choose over 300 in-demand skills and get access to 1000+ hours of video content for FREE in various technologies like Data Science, Cybersecurity, Project Management & Leadership, Digital Marketing, and much more.
Don't forget to take the quiz at 04:26!
To learn more about Deep Learning, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1
Watch more videos on Deep Learning: https://www.youtube.com/watch?v=FbxTVRfQFuI&list;=PLEiEAq2VkUUIYQ-mMRAGilfOKyWKpHSip
#DeepLearning #WhatIsDeepLearning #DeepLearningTutorial #DeepLearningCourse #DeepLearningExplained #Simplilearn
Simplilearn’s Deep Learning course will transform you into an expert in Deep Learning techniques using TensorFlow, the open-source software library designed to conduct machine learning & deep neural network research. With our Deep Learning course, you'll master Deep Learning and TensorFlow concepts, learn to implement algorithms, build artificial neural networks and traverse layers of data abstraction to understand the power of data and prepare you for your new role as Deep Learning scientist.
Why Deep Learning?
It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial neural networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in Deep Learning models, learn to operate TensorFlow to manage neural networks and interpret the results. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.
You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement Deep Learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
4. Build Deep Learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of artificial neural networks
6. Troubleshoot and improve Deep Learning models
7. Build your own Deep Learning project
8. Differentiate between machine learning, Deep Learning and artificial intelligence
There is booming demand for skilled Deep Learning engineers across a wide range of industries, making this Deep Learning course with TensorFlow training well-suited for professionals at the intermediate to advanced level of experience. We recommend this Deep Learning online course particularly for the following professionals:
1. Software engineers
2. Data scientists
3. Data analysts
4. Statisticians with an interest in Deep Learning
Learn more at: https://www.simplilearn.com/deep-learning-course-with-tensorflow-training?utm_campaign=DeepLearning&utm;_medium=Description&utm;_source=youtube
For more information about Simplilearn’s courses, visit:
- Facebook: https://www.facebook.com/Simplilearn
- Twitter: https://twitter.com/simplilearn
- LinkedIn: https://www.linkedin.com/company/simplilearn/
- Website: https://www.simplilearn.com
Get the Android app: http://bit.ly/1WlVo4u
Get the iOS app: http://apple.co/1HIO5J0
- published: 03 Jun 2019
- views: 866159
19:13
But what is a neural network? | Chapter 1, Deep learning
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interacti...
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
Additional funding for this project provided by Amplify Partners
Typo correction: At 14 minutes 45 seconds, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning!
https://github.com/mnielsen/neural-networks-and-deep-learning
I also highly recommend Chris Olah's blog: http://colah.github.io/
For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs
For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville.
Also, the publication Distill is just utterly beautiful: https://distill.pub/
Lion photo by Kevin Pluck
-----------------
Timeline:
0:00 - Introduction example
1:07 - Series preview
2:42 - What are neurons?
3:35 - Introducing layers
5:31 - Why layers?
8:38 - Edge detection example
11:34 - Counting weights and biases
12:30 - How learning relates
13:26 - Notation and linear algebra
15:17 - Recap
16:27 - Some final words
17:03 - ReLU vs Sigmoid
------------------
Animations largely made using manim, a scrappy open source python library. https://github.com/3b1b/manim
If you want to check it out, I feel compelled to warn you that it's not the most well-documented tool, and has many other quirks you might expect in a library someone wrote with only their own use in mind.
Music by Vincent Rubinetti.
Download the music on Bandcamp:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
Stream the music on Spotify:
https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u
If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then "add subtitles/cc". I really appreciate those who do this, as it helps make the lessons accessible to more people.
------------------
3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown
https://wn.com/But_What_Is_A_Neural_Network_|_Chapter_1,_Deep_Learning
What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
Additional funding for this project provided by Amplify Partners
Typo correction: At 14 minutes 45 seconds, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning!
https://github.com/mnielsen/neural-networks-and-deep-learning
I also highly recommend Chris Olah's blog: http://colah.github.io/
For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs
For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville.
Also, the publication Distill is just utterly beautiful: https://distill.pub/
Lion photo by Kevin Pluck
-----------------
Timeline:
0:00 - Introduction example
1:07 - Series preview
2:42 - What are neurons?
3:35 - Introducing layers
5:31 - Why layers?
8:38 - Edge detection example
11:34 - Counting weights and biases
12:30 - How learning relates
13:26 - Notation and linear algebra
15:17 - Recap
16:27 - Some final words
17:03 - ReLU vs Sigmoid
------------------
Animations largely made using manim, a scrappy open source python library. https://github.com/3b1b/manim
If you want to check it out, I feel compelled to warn you that it's not the most well-documented tool, and has many other quirks you might expect in a library someone wrote with only their own use in mind.
Music by Vincent Rubinetti.
Download the music on Bandcamp:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
Stream the music on Spotify:
https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u
If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then "add subtitles/cc". I really appreciate those who do this, as it helps make the lessons accessible to more people.
------------------
3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown
- published: 05 Oct 2017
- views: 11703823
1:25:39
Deep Learning Crash Course for Beginners
Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute beginners with no experi...
Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute beginners with no experience in programming. You will learn the key ideas behind deep learning without any code.
You'll learn about Neural Networks, Machine Learning constructs like Supervised, Unsupervised and Reinforcement Learning, the various types of Neural Network architectures, and more.
✏️ Course developed by Jason Dsouza. Check out his YouTube channel: http://youtube.com/jasmcaus
⭐️ Course Contents ⭐️
⌨️ (0:00) Introduction
⌨️ (1:18) What is Deep Learning
⌨️ (5:25) Introduction to Neural Networks
⌨️ (6:12) How do Neural Networks LEARN?
⌨️ (12:06) Core terminologies used in Deep Learning
⌨️ (12:11) Activation Functions
⌨️ (22:36) Loss Functions
⌨️ (23:42) Optimizers
⌨️ (30:10) Parameters vs Hyperparameters
⌨️ (32:03) Epochs, Batches & Iterations
⌨️ (34:24) Conclusion to Terminologies
⌨️ (35:18) Introduction to Learning
⌨️ (35:34) Supervised Learning
⌨️ (40:21) Unsupervised Learning
⌨️ (43:38) Reinforcement Learning
⌨️ (46:25) Regularization
⌨️ (51:25) Introduction to Neural Network Architectures
⌨️ (51:37) Fully-Connected Feedforward Neural Nets
⌨️ (54:05) Recurrent Neural Nets
⌨️ (1:04:40) Convolutional Neural Nets
⌨️ (1:08:07) Introduction to the 5 Steps to EVERY Deep Learning Model
⌨️ (1:08:23) 1. Gathering Data
⌨️ (1:11:27) 2. Preprocessing the Data
⌨️ (1:19:05) 3. Training your Model
⌨️ (1:19:33) 4. Evaluating your Model
⌨️ (1:19:55) 5. Optimizing your Model's Accuracy
⌨️ (1:25:15) Conclusion to the Course
--
Learn to code for free and get a developer job: https://www.freecodecamp.org
Read hundreds of articles on programming: https://freecodecamp.org/news
And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
https://wn.com/Deep_Learning_Crash_Course_For_Beginners
Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute beginners with no experience in programming. You will learn the key ideas behind deep learning without any code.
You'll learn about Neural Networks, Machine Learning constructs like Supervised, Unsupervised and Reinforcement Learning, the various types of Neural Network architectures, and more.
✏️ Course developed by Jason Dsouza. Check out his YouTube channel: http://youtube.com/jasmcaus
⭐️ Course Contents ⭐️
⌨️ (0:00) Introduction
⌨️ (1:18) What is Deep Learning
⌨️ (5:25) Introduction to Neural Networks
⌨️ (6:12) How do Neural Networks LEARN?
⌨️ (12:06) Core terminologies used in Deep Learning
⌨️ (12:11) Activation Functions
⌨️ (22:36) Loss Functions
⌨️ (23:42) Optimizers
⌨️ (30:10) Parameters vs Hyperparameters
⌨️ (32:03) Epochs, Batches & Iterations
⌨️ (34:24) Conclusion to Terminologies
⌨️ (35:18) Introduction to Learning
⌨️ (35:34) Supervised Learning
⌨️ (40:21) Unsupervised Learning
⌨️ (43:38) Reinforcement Learning
⌨️ (46:25) Regularization
⌨️ (51:25) Introduction to Neural Network Architectures
⌨️ (51:37) Fully-Connected Feedforward Neural Nets
⌨️ (54:05) Recurrent Neural Nets
⌨️ (1:04:40) Convolutional Neural Nets
⌨️ (1:08:07) Introduction to the 5 Steps to EVERY Deep Learning Model
⌨️ (1:08:23) 1. Gathering Data
⌨️ (1:11:27) 2. Preprocessing the Data
⌨️ (1:19:05) 3. Training your Model
⌨️ (1:19:33) 4. Evaluating your Model
⌨️ (1:19:55) 5. Optimizing your Model's Accuracy
⌨️ (1:25:15) Conclusion to the Course
--
Learn to code for free and get a developer job: https://www.freecodecamp.org
Read hundreds of articles on programming: https://freecodecamp.org/news
And subscribe for new videos on technology every day: https://youtube.com/subscription_center?add_user=freecodecamp
- published: 30 Jul 2020
- views: 380764
0:00
Cancer Detection Using Deep Learning | Deep Learning Projects | Edureka | DL Rewind - 4
🔥Edureka Deep Learning With TensorFlow (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎): https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka video on 𝐂𝐚𝐧𝐜𝐞𝐫 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐔𝐬𝐢...
🔥Edureka Deep Learning With TensorFlow (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎): https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka video on 𝐂𝐚𝐧𝐜𝐞𝐫 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐔𝐬𝐢𝐧𝐠 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, will help you understand how to develop models using Convolution Neural Networks. We will also have a discussion on improving model accuracy using pretrained models.
🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s
🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV
📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/
---------------------------------------Edureka Post Graduate Courses-------------------------------------------
🔵 Artificial and Machine Learning PGD: https://bit.ly/3AylL0q
#edureka #edurekadeeplearning #deeplearningwithtensorflow #cancerdetectionusingdeeplearning #convolutionneuralnetworks #deeplearningpretrainedmodels #deepearningtutorial #edurekatraining
---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------
🔵 Data Science Online Training: https://bit.ly/2NCT239
🟣 Python Online Training: https://bit.ly/2CQYGN7
🔵 AWS Online Training: https://bit.ly/2ZnbW3s
🟣 RPA Online Training: https://bit.ly/2Zd0ac0
🔵 DevOps Online Training: https://bit.ly/2BPwXf0
🟣 Big Data Online Training: https://bit.ly/3g8zksu
🔵 Java Online Training: https://bit.ly/31rxJcY
---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬---------
🟣Machine Learning Engineer Masters Program: https://bit.ly/388NXJi
🔵DevOps Engineer Masters Program: https://bit.ly/2B9tZCp
🟣Cloud Architect Masters Program: https://bit.ly/3i9z0eJ
🔵Data Scientist Masters Program: https://bit.ly/2YHaolS
🟣Big Data Architect Masters Program: https://bit.ly/31qrOVv
🔵Business Intelligence Masters Program: https://bit.ly/2BPLtn2
-----------------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝐆𝐏 𝐂𝐨𝐮𝐫𝐬𝐞𝐬---------------
🔵Artificial and Machine Learning PGP: https://bit.ly/2Ziy7b1
🟣CyberSecurity PGP: https://bit.ly/3eHvI0h
🔵Digital Marketing PGP: https://bit.ly/38cqdnz
🟣Big Data Engineering PGP: https://bit.ly/3eTSyBC
🔵Data Science PGP: https://bit.ly/3dIeYV9
🟣Cloud Computing PGP: https://bit.ly/2B9tHLP
----------------------------------
🔅🔅How it Works?
1. This is a 5 Week Instructor led Online Course.
2. Course consists of 30 hours of online classes, 20 hours of assignment, 20 hours of project
3. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
4. You will get Lifetime Access to the recordings in the LMS.
5. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!
- - - - - - - - - - - - - -
🔅🔅About the Course
Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.
- - - - - - - - - - - - - -
For Online Training and Certification, Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information
https://wn.com/Cancer_Detection_Using_Deep_Learning_|_Deep_Learning_Projects_|_Edureka_|_Dl_Rewind_4
🔥Edureka Deep Learning With TensorFlow (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎): https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka video on 𝐂𝐚𝐧𝐜𝐞𝐫 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐔𝐬𝐢𝐧𝐠 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, will help you understand how to develop models using Convolution Neural Networks. We will also have a discussion on improving model accuracy using pretrained models.
🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s
🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV
📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/
---------------------------------------Edureka Post Graduate Courses-------------------------------------------
🔵 Artificial and Machine Learning PGD: https://bit.ly/3AylL0q
#edureka #edurekadeeplearning #deeplearningwithtensorflow #cancerdetectionusingdeeplearning #convolutionneuralnetworks #deeplearningpretrainedmodels #deepearningtutorial #edurekatraining
---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------
🔵 Data Science Online Training: https://bit.ly/2NCT239
🟣 Python Online Training: https://bit.ly/2CQYGN7
🔵 AWS Online Training: https://bit.ly/2ZnbW3s
🟣 RPA Online Training: https://bit.ly/2Zd0ac0
🔵 DevOps Online Training: https://bit.ly/2BPwXf0
🟣 Big Data Online Training: https://bit.ly/3g8zksu
🔵 Java Online Training: https://bit.ly/31rxJcY
---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬---------
🟣Machine Learning Engineer Masters Program: https://bit.ly/388NXJi
🔵DevOps Engineer Masters Program: https://bit.ly/2B9tZCp
🟣Cloud Architect Masters Program: https://bit.ly/3i9z0eJ
🔵Data Scientist Masters Program: https://bit.ly/2YHaolS
🟣Big Data Architect Masters Program: https://bit.ly/31qrOVv
🔵Business Intelligence Masters Program: https://bit.ly/2BPLtn2
-----------------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝐆𝐏 𝐂𝐨𝐮𝐫𝐬𝐞𝐬---------------
🔵Artificial and Machine Learning PGP: https://bit.ly/2Ziy7b1
🟣CyberSecurity PGP: https://bit.ly/3eHvI0h
🔵Digital Marketing PGP: https://bit.ly/38cqdnz
🟣Big Data Engineering PGP: https://bit.ly/3eTSyBC
🔵Data Science PGP: https://bit.ly/3dIeYV9
🟣Cloud Computing PGP: https://bit.ly/2B9tHLP
----------------------------------
🔅🔅How it Works?
1. This is a 5 Week Instructor led Online Course.
2. Course consists of 30 hours of online classes, 20 hours of assignment, 20 hours of project
3. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
4. You will get Lifetime Access to the recordings in the LMS.
5. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!
- - - - - - - - - - - - - -
🔅🔅About the Course
Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.
- - - - - - - - - - - - - -
For Online Training and Certification, Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information
- published: 05 Nov 2021
- views: 0
6:02:26
Deep Learning Full Course - Learn Deep Learning in 6 Hours | Deep Learning Tutorial | Edureka
** AI & Deep Learning with TensorFlow (Use Code: YOUTUBE20): https://www.edureka.co/ai-deep-learning-with-tensorflow **
This Edureka Deep Learning Full Course v...
** AI & Deep Learning with TensorFlow (Use Code: YOUTUBE20): https://www.edureka.co/ai-deep-learning-with-tensorflow **
This Edureka Deep Learning Full Course video will help you understand and learn Deep Learning & Tensorflow in detail. This Deep Learning Tutorial is ideal for both beginners as well as professionals who want to master Deep Learning Algorithms. Below are the topics covered in this Deep Learning tutorial video:
00:00 Introduction
3:11 What is Deep Learning
3:55 Why Artificial Intelligence?
5:48 What is AI?
6:53 Applications of AI
8:43 Machine Learning
10:28 Types of Machine Learning
10:33 Supervised Learning
11:43 Unsupervised Learning
13:08 Reinforcement Learning
14:38 Limitations of Machine Learning
16:08 Deep Learning to the Rescue
19:28 What is Deep Learning?
22:58 Deep Learning Example
24:28 Deep Learning Applications
25:48 Deep Learning Tutorial
27:08 Understanding Deep Learning With an Analogy
29:58 How Deep Learning works?
31:12 Why We need Artificial Neuron?
32:58 Perceptron Learning Algorithm
36:13 Types of Activation Functions
41:33 Single Layer Perceptron Use-case
42:33 What is TensorFlow?
44:18 Tensorflow Code Basics
49:08 TensorFlow Example
59:13 What is a Computational Graph?
1:27:08 Limitations of Single Layer Perceptron
1:28:08 Multilayer Perceptron
1:29:18 How it works?
1:29:23 What is Backpropagation?
1:30:23 Backpropagation Learning Algorithm
1:34:43 Multilayer Perceptron Use-case
1:37:48 Top 8 Deep Learning Frameworks
1:38:18 Chainer
1:39:18 CNTK
1:40:48 Caffe
1:42:28 MXNet
1:43:33 Deeplearning4j
1:45:23 Keras
1:46:58 PyTorch
1:48:23 TensorFlow
1:50:23 TensorFlow Tutorial
1:50:43 Rock or Mine Prediction Use-case
1:52:53 How to Create This Model?
1:54:13 What are Tensors?
1:54:38 Tensor Rank
1:55:58 What is TensorFlow?
2:02:28 Graph Visualization
2:05:10 Constant, Placeholder & Variables
2:08:55 Creating A Model
2:17:06 Reducing The Loss
2:18:31 Batch Gradient Descent
2:22:01 Implementing Rock or Mine Prediction Use-case
2:36:24 Artificial Neural Network Tutorial
2:39:29 Why Neural Network?
2:40:29 Problems Before Neural Network
2:42:09 What is Artificial Neural Network?
2:44:04 How It Works?
2:46:24 Perceptron Learning Algorithm - Beer Analogy
2:52:24 Multilayer Perceptron
2:53:34 Artificial Neutral Network
2:54:24 Training A Neural Network
3:05:54 Applications of Network Networks
3:09:04 Backpropagation & Gradient Descent Tutorial
3:09:49 Perceptron
3:10:44 How does the Network Learn?
3:11:09 MNIST Dataset
3:11:59 Cost Function
3:13:54 Finding Local Minima
3:16:09 Gradient Descent Learning
3:17:19 Back Propagation
3:21:29 Recurrent Neural Networks
3:22:04 Why not Feedforward Network?
3:24:29 What is Recurrent Neural Networks?
3:29:24 Training A Recurrent Neural Network
3:29:49 Vanishing & Exploding Gradient Problem
3:34:09 Long Short Term Memory Networks
3:51:04 Convolutional Neural Network
3:51:29 How A Computer Reads An Image?
3:52:14 Why Not Fully Connected Network?
3:53:29 What Convolutional Neural Network?
3:54:04 How CNN Works?
3:54:39 Convolution Layer
3:59:04 ReLU Layer
4:03:49 Fully Connected Layer
4:11:59 Autoencoders Tutorial
4:13:49 PCA vs Autoencoders
4:15:14 Introduction to Autoencoders
4:17:09 Properties of Autoencoders
4:18:09 Training Autoencoders
4:19:14 Architecture of Autoencoders
4:23:49 Types of Autoencoders
4:25:49 Convolutional Autoencoders
4:26:44 Sparse Autoencoders
4:28:29 Deep Autoencoders
4:30:29 Contractive Autoencoders
4:31:54 Demo
4:35:09 Restricted Boltzmann Machine
4:38:54 Working of RBMs
4:40:29 RBM: Energy-Based Model
4:42:34 RBM: Probabilistic Model
4:42:54 RBM Training
4:44:09 RBM: Training to Prediction
4:44:39 RBM: Example
4:46:29 TensorFlow Object Detection
4:47:34 What is Object Detection?
4:48:24 Object Detection Applications
4:51:04 Workflow of Object Detection
4:52:49 Object Detection in TensorFlow
4:53:59 Object Detection Demo
5:10:44 Creating Chatbots Using Tensorflow
5:12:14 What is Chatbots?
5:12:19 How Does ChatBot Works?
5:14:44 Applications of Chatbot
5:15:54 Layers of Chatbot
5:16:14 Natural Language Processing
5:19:59 Demo
5:21:44 Layers of Chatbot
5:21:59 Deep Learning Interview Questions
--------------------------------------------------------------------------------------------------------
PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai
Post Graduate Certification in Data Science with IIT Guwahati - https://www.edureka.co/post-graduate/data-science-program
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)
Instagram: https://www.instagram.com/edureka_learning
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).
https://wn.com/Deep_Learning_Full_Course_Learn_Deep_Learning_In_6_Hours_|_Deep_Learning_Tutorial_|_Edureka
** AI & Deep Learning with TensorFlow (Use Code: YOUTUBE20): https://www.edureka.co/ai-deep-learning-with-tensorflow **
This Edureka Deep Learning Full Course video will help you understand and learn Deep Learning & Tensorflow in detail. This Deep Learning Tutorial is ideal for both beginners as well as professionals who want to master Deep Learning Algorithms. Below are the topics covered in this Deep Learning tutorial video:
00:00 Introduction
3:11 What is Deep Learning
3:55 Why Artificial Intelligence?
5:48 What is AI?
6:53 Applications of AI
8:43 Machine Learning
10:28 Types of Machine Learning
10:33 Supervised Learning
11:43 Unsupervised Learning
13:08 Reinforcement Learning
14:38 Limitations of Machine Learning
16:08 Deep Learning to the Rescue
19:28 What is Deep Learning?
22:58 Deep Learning Example
24:28 Deep Learning Applications
25:48 Deep Learning Tutorial
27:08 Understanding Deep Learning With an Analogy
29:58 How Deep Learning works?
31:12 Why We need Artificial Neuron?
32:58 Perceptron Learning Algorithm
36:13 Types of Activation Functions
41:33 Single Layer Perceptron Use-case
42:33 What is TensorFlow?
44:18 Tensorflow Code Basics
49:08 TensorFlow Example
59:13 What is a Computational Graph?
1:27:08 Limitations of Single Layer Perceptron
1:28:08 Multilayer Perceptron
1:29:18 How it works?
1:29:23 What is Backpropagation?
1:30:23 Backpropagation Learning Algorithm
1:34:43 Multilayer Perceptron Use-case
1:37:48 Top 8 Deep Learning Frameworks
1:38:18 Chainer
1:39:18 CNTK
1:40:48 Caffe
1:42:28 MXNet
1:43:33 Deeplearning4j
1:45:23 Keras
1:46:58 PyTorch
1:48:23 TensorFlow
1:50:23 TensorFlow Tutorial
1:50:43 Rock or Mine Prediction Use-case
1:52:53 How to Create This Model?
1:54:13 What are Tensors?
1:54:38 Tensor Rank
1:55:58 What is TensorFlow?
2:02:28 Graph Visualization
2:05:10 Constant, Placeholder & Variables
2:08:55 Creating A Model
2:17:06 Reducing The Loss
2:18:31 Batch Gradient Descent
2:22:01 Implementing Rock or Mine Prediction Use-case
2:36:24 Artificial Neural Network Tutorial
2:39:29 Why Neural Network?
2:40:29 Problems Before Neural Network
2:42:09 What is Artificial Neural Network?
2:44:04 How It Works?
2:46:24 Perceptron Learning Algorithm - Beer Analogy
2:52:24 Multilayer Perceptron
2:53:34 Artificial Neutral Network
2:54:24 Training A Neural Network
3:05:54 Applications of Network Networks
3:09:04 Backpropagation & Gradient Descent Tutorial
3:09:49 Perceptron
3:10:44 How does the Network Learn?
3:11:09 MNIST Dataset
3:11:59 Cost Function
3:13:54 Finding Local Minima
3:16:09 Gradient Descent Learning
3:17:19 Back Propagation
3:21:29 Recurrent Neural Networks
3:22:04 Why not Feedforward Network?
3:24:29 What is Recurrent Neural Networks?
3:29:24 Training A Recurrent Neural Network
3:29:49 Vanishing & Exploding Gradient Problem
3:34:09 Long Short Term Memory Networks
3:51:04 Convolutional Neural Network
3:51:29 How A Computer Reads An Image?
3:52:14 Why Not Fully Connected Network?
3:53:29 What Convolutional Neural Network?
3:54:04 How CNN Works?
3:54:39 Convolution Layer
3:59:04 ReLU Layer
4:03:49 Fully Connected Layer
4:11:59 Autoencoders Tutorial
4:13:49 PCA vs Autoencoders
4:15:14 Introduction to Autoencoders
4:17:09 Properties of Autoencoders
4:18:09 Training Autoencoders
4:19:14 Architecture of Autoencoders
4:23:49 Types of Autoencoders
4:25:49 Convolutional Autoencoders
4:26:44 Sparse Autoencoders
4:28:29 Deep Autoencoders
4:30:29 Contractive Autoencoders
4:31:54 Demo
4:35:09 Restricted Boltzmann Machine
4:38:54 Working of RBMs
4:40:29 RBM: Energy-Based Model
4:42:34 RBM: Probabilistic Model
4:42:54 RBM Training
4:44:09 RBM: Training to Prediction
4:44:39 RBM: Example
4:46:29 TensorFlow Object Detection
4:47:34 What is Object Detection?
4:48:24 Object Detection Applications
4:51:04 Workflow of Object Detection
4:52:49 Object Detection in TensorFlow
4:53:59 Object Detection Demo
5:10:44 Creating Chatbots Using Tensorflow
5:12:14 What is Chatbots?
5:12:19 How Does ChatBot Works?
5:14:44 Applications of Chatbot
5:15:54 Layers of Chatbot
5:16:14 Natural Language Processing
5:19:59 Demo
5:21:44 Layers of Chatbot
5:21:59 Deep Learning Interview Questions
--------------------------------------------------------------------------------------------------------
PG in Artificial Intelligence and Machine Learning with NIT Warangal : https://www.edureka.co/post-graduate/machine-learning-and-ai
Post Graduate Certification in Data Science with IIT Guwahati - https://www.edureka.co/post-graduate/data-science-program
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)
Instagram: https://www.instagram.com/edureka_learning
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
For more information, please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free).
- published: 08 Sep 2019
- views: 422571
1:08:06
Deep Learning Basics: Introduction and Overview
An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks ha...
An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks have inspired and energized an entire new generation of researchers. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.
INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/deep-learning-basics-slides
Playlist: http://bit.ly/deep-learning-playlist
Blog post: https://link.medium.com/TkE476jw2T
OUTLINE:
0:00 - Introduction
0:53 - Deep learning in one slide
4:55 - History of ideas and tools
9:43 - Simple example in TensorFlow
11:36 - TensorFlow in one slide
13:32 - Deep learning is representation learning
16:02 - Why deep learning (and why not)
22:00 - Challenges for supervised learning
38:27 - Key low-level concepts
46:15 - Higher-level methods
1:06:00 - Toward artificial general intelligence
CONNECT:
- If you enjoyed this video, please subscribe to this channel.
- Twitter: https://twitter.com/lexfridman
- LinkedIn: https://www.linkedin.com/in/lexfridman
- Facebook: https://www.facebook.com/lexfridman
- Instagram: https://www.instagram.com/lexfridman
https://wn.com/Deep_Learning_Basics_Introduction_And_Overview
An introductory lecture for MIT course 6.S094 on the basics of deep learning including a few key ideas, subfields, and the big picture of why neural networks have inspired and energized an entire new generation of researchers. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.
INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/deep-learning-basics-slides
Playlist: http://bit.ly/deep-learning-playlist
Blog post: https://link.medium.com/TkE476jw2T
OUTLINE:
0:00 - Introduction
0:53 - Deep learning in one slide
4:55 - History of ideas and tools
9:43 - Simple example in TensorFlow
11:36 - TensorFlow in one slide
13:32 - Deep learning is representation learning
16:02 - Why deep learning (and why not)
22:00 - Challenges for supervised learning
38:27 - Key low-level concepts
46:15 - Higher-level methods
1:06:00 - Toward artificial general intelligence
CONNECT:
- If you enjoyed this video, please subscribe to this channel.
- Twitter: https://twitter.com/lexfridman
- LinkedIn: https://www.linkedin.com/in/lexfridman
- Facebook: https://www.facebook.com/lexfridman
- Instagram: https://www.instagram.com/lexfridman
- published: 11 Jan 2019
- views: 1388038
56:36
MIT Introduction to Deep Learning | 6.S191
MIT Introduction to Deep Learning 6.S191: Lecture 1
*New 2021 Edition*
Foundations of Deep Learning
Lecturer: Alexander Amini
For all lectures, slides, and lab...
MIT Introduction to Deep Learning 6.S191: Lecture 1
*New 2021 Edition*
Foundations of Deep Learning
Lecturer: Alexander Amini
For all lectures, slides, and lab materials: http://introtodeeplearning.com/
Lecture Outline
0:00 - Introduction
4:48 - Course information
10:18 - Why deep learning?
12:28 - The perceptron
14:42 - Activation functions
17:48 - Perceptron example
21:43 - From perceptrons to neural networks
27:42 - Applying neural networks
30:21 - Loss functions
33:23 - Training and gradient descent
38:05 - Backpropagation
43:06 - Setting the learning rate
47:17 - Batched gradient descent
49:49 - Regularization: dropout and early stopping
55:55 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us on @MITDeepLearning on Twitter and Instagram to stay fully-connected!!
https://wn.com/Mit_Introduction_To_Deep_Learning_|_6.S191
MIT Introduction to Deep Learning 6.S191: Lecture 1
*New 2021 Edition*
Foundations of Deep Learning
Lecturer: Alexander Amini
For all lectures, slides, and lab materials: http://introtodeeplearning.com/
Lecture Outline
0:00 - Introduction
4:48 - Course information
10:18 - Why deep learning?
12:28 - The perceptron
14:42 - Activation functions
17:48 - Perceptron example
21:43 - From perceptrons to neural networks
27:42 - Applying neural networks
30:21 - Loss functions
33:23 - Training and gradient descent
38:05 - Backpropagation
43:06 - Setting the learning rate
47:17 - Batched gradient descent
49:49 - Regularization: dropout and early stopping
55:55 - Summary
Subscribe to stay up to date with new deep learning lectures at MIT, or follow us on @MITDeepLearning on Twitter and Instagram to stay fully-connected!!
- published: 05 Feb 2021
- views: 480940
21:01
Gradient descent, how neural networks learn | Chapter 2, Deep learning
Enjoy these videos? Consider sharing one or two.
Help fund future projects: https://www.patreon.com/3blue1brown
Special thanks to these supporters: http://3b1b...
Enjoy these videos? Consider sharing one or two.
Help fund future projects: https://www.patreon.com/3blue1brown
Special thanks to these supporters: http://3b1b.co/nn2-thanks
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
This video was supported by Amplify Partners.
For any early-stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com
To learn more, I highly recommend the book by Michael Nielsen
http://neuralnetworksanddeeplearning.com/
The book walks through the code behind the example in these videos, which you can find here:
https://github.com/mnielsen/neural-networks-and-deep-learning
MNIST database:
http://yann.lecun.com/exdb/mnist/
Also check out Chris Olah's blog:
http://colah.github.io/
His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great.
And if you like that, you'll *love* the publications at distill:
https://distill.pub/
For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs
"But I've already voraciously consumed Nielsen's, Olah's and Welch's works", I hear you say. Well well, look at you then. That being the case, I might recommend that you continue on with the book "Deep Learning" by Goodfellow, Bengio, and Courville.
Thanks to Lisha Li (@lishali88) for her contributions at the end, and for letting me pick her brain so much about the material. Here are the articles she referenced at the end:
https://arxiv.org/abs/1611.03530
https://arxiv.org/abs/1706.05394
https://arxiv.org/abs/1412.0233
Music by Vincent Rubinetti:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
-------------------
Video timeline
0:00 - Introduction
0:30 - Recap
1:49 - Using training data
3:01 - Cost functions
6:55 - Gradient descent
11:18 - More on gradient vectors
12:19 - Gradient descent recap
13:01 - Analyzing the network
16:37 - Learning more
17:38 - Lisha Li interview
19:58 - Closing thoughts
------------------
3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown
https://wn.com/Gradient_Descent,_How_Neural_Networks_Learn_|_Chapter_2,_Deep_Learning
Enjoy these videos? Consider sharing one or two.
Help fund future projects: https://www.patreon.com/3blue1brown
Special thanks to these supporters: http://3b1b.co/nn2-thanks
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks
This video was supported by Amplify Partners.
For any early-stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com
To learn more, I highly recommend the book by Michael Nielsen
http://neuralnetworksanddeeplearning.com/
The book walks through the code behind the example in these videos, which you can find here:
https://github.com/mnielsen/neural-networks-and-deep-learning
MNIST database:
http://yann.lecun.com/exdb/mnist/
Also check out Chris Olah's blog:
http://colah.github.io/
His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great.
And if you like that, you'll *love* the publications at distill:
https://distill.pub/
For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs
"But I've already voraciously consumed Nielsen's, Olah's and Welch's works", I hear you say. Well well, look at you then. That being the case, I might recommend that you continue on with the book "Deep Learning" by Goodfellow, Bengio, and Courville.
Thanks to Lisha Li (@lishali88) for her contributions at the end, and for letting me pick her brain so much about the material. Here are the articles she referenced at the end:
https://arxiv.org/abs/1611.03530
https://arxiv.org/abs/1706.05394
https://arxiv.org/abs/1412.0233
Music by Vincent Rubinetti:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
-------------------
Video timeline
0:00 - Introduction
0:30 - Recap
1:49 - Using training data
3:01 - Cost functions
6:55 - Gradient descent
11:18 - More on gradient vectors
12:19 - Gradient descent recap
13:01 - Analyzing the network
16:37 - Learning more
17:38 - Lisha Li interview
19:58 - Closing thoughts
------------------
3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown
- published: 16 Oct 2017
- views: 4949392
3:48
Introduction to Deep Learning: Machine Learning vs. Deep Learning
Learn about the differences between deep learning and machine learning in this MATLAB® Tech Talk.
- MATLAB for Deep Learning: http://bit.ly/2Dl0jm4
Walk throu...
Learn about the differences between deep learning and machine learning in this MATLAB® Tech Talk.
- MATLAB for Deep Learning: http://bit.ly/2Dl0jm4
Walk through several examples, and learn how to decide which method to use.
Learn more about Deep Learning: https://goo.gl/F8tBZi
Download a trial: https://goo.gl/PSa78r
The video outlines the specific workflow for solving a machine learning problem.
The video also outlines the differing requirements for machine learning and deep learning. You’ll learn about the key questions to ask before deciding between machine learning and deep learning.
The choice between machine learning or deep learning depends on your data and the problem you’re trying to solve. MATLAB can help you with both of these techniques – either separately or as a combined approach.
https://wn.com/Introduction_To_Deep_Learning_Machine_Learning_Vs._Deep_Learning
Learn about the differences between deep learning and machine learning in this MATLAB® Tech Talk.
- MATLAB for Deep Learning: http://bit.ly/2Dl0jm4
Walk through several examples, and learn how to decide which method to use.
Learn more about Deep Learning: https://goo.gl/F8tBZi
Download a trial: https://goo.gl/PSa78r
The video outlines the specific workflow for solving a machine learning problem.
The video also outlines the differing requirements for machine learning and deep learning. You’ll learn about the key questions to ask before deciding between machine learning and deep learning.
The choice between machine learning or deep learning depends on your data and the problem you’re trying to solve. MATLAB can help you with both of these techniques – either separately or as a combined approach.
- published: 04 Apr 2017
- views: 390791
9:09
Neural Network Architectures & Deep Learning
This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional...
This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders.
Book website: http://databookuw.com/
Steve Brunton's website: eigensteve.com
Follow updates on Twitter @eigensteve
This video is part of a playlist "Intro to Data Science":
https://www.youtube.com/playlist?list=PLMrJAkhIeNNQV7wi9r7Kut8liLFMWQOXn
https://wn.com/Neural_Network_Architectures_Deep_Learning
This video describes the variety of neural network architectures available to solve various problems in science ad engineering. Examples include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and autoencoders.
Book website: http://databookuw.com/
Steve Brunton's website: eigensteve.com
Follow updates on Twitter @eigensteve
This video is part of a playlist "Intro to Data Science":
https://www.youtube.com/playlist?list=PLMrJAkhIeNNQV7wi9r7Kut8liLFMWQOXn
- published: 06 Jun 2019
- views: 629701