- published: 30 Apr 2012
- views: 7048
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If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product groups (Bing QnA team) to discuss the technical challenges faced in the real-world scenarios and highlight the research need.
- published: 22 Jun 2016
- views: 395
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models.
Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better suited to this type of task because of their ability to capture higher-order syntax. Two papers, “Applying deep learning to answer selection: a study and an open task” (Feng et. al. 2015) and “LSTM-based deep learning models for non-factoid answer selection” (Tan et. al. 2016), are recent examples which have applied deep learning to question-answering tasks with good results.
Feng et. al. used an in-house Java framework for their work, and Tan et. al. built their model entirely from Theano. This tutorial will demonstrate how to replicate the models used by each group using the popular open-source framework Keras, adding custom functions to include recent advances from the neural networks community.
- published: 04 Oct 2016
- views: 2526
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go beyond
answering fact-based questions. Watson has been hugely successful
at answering fact-based questions, but to solve hard AI tasks like
passing science tests and understanding narratives, we need to go
beyond simple facts. In this talk, I discuss how the systems I have
most recently worked on have approached this problem. Watson for
Healthcare answers Doctor's Dilemma medical competition questions,
and WatsonPaths answers medical test preparation questions. These
systems have achieved some success, but there is still a lot more
to be done. Based on my experiences working on these systems, I
discuss what I think the priorities should be going forward. First,
to deal with the richness of human knowledge, we need to move...
- published: 11 Apr 2015
- views: 1776
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images
-------------------------------------------------------------------------------
Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
For additional learning opportunities please visit:
http://stanfordonline.stanford.edu/
- published: 03 Apr 2017
- views: 965
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed the video :) thanks so much ♥
───────────────────
▶ Please subscribe to update new videos.
Subscribe To Update New Lesson:
https://www.youtube.com/channel/UCV1h_cBE0Drdx19qkTM0WNw?sub_confirmation=1
- published: 03 Sep 2016
- views: 330964
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly.
2. "What are your strengths?"
This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for.
3. "What are your weaknesses?"
For this answer, you should display a weakness that can be seen as a strength. There are many types of answers that will work. Some answers will be good answers for certain jobs, while the same answer will be a bad answer for a different job. Select an answer that will work for the position you are applying for.
4. "Where do you see yourself in five years?"
This question primarily depends on where you are in your career. A person with 5 years of experience will have different goals than a person with no work experience.This question is asked to see how serious a candidate is about his or her career. Some people might not know their goals, and some people might have goals of becoming rich and retiring early. Those are incorrect answers for this question. The type of answer you want to give is an ambitious answer that shows you really love your career. A good interviewer will read between the lines and find out if a person is going to be a hard worker or just a mediocre one. Being descriptive and shooting for a big goal is something interviewers want to hear.
5. "What do you know about our company?"
A typical job interview question, asked to find out how much company research you have conducted, is "What do you know about this company?" Prepare in advance, and in a word, research, so you can provide relevant and current information about your prospective employer to the interviewer.
6. "Are you good at dealing with change?"
Dealing with change is common in the work place. A simple yes will not be sufficient to impress the interviewer. This is another type of question where everyone will have similar answers. Of course everyone is going to claim being excellent dealing with change. You got to communicate that you are really good at dealing with change.
7. "Do you work well under pressure?"
In most cases, the best answer to this question is answering yes. Working well under pressure is a good trait to have. However, I think if you answer that you work the same with pressure and without pressure, the interviewer will be more impressed. However, you will need to explain in words why this is better.
8. "How do you make important decisions?"
There are many ways to answer this question, and if you have a reasonable method of making decisions, it will probably be sufficient. One answer I thought of included not being afraid of asking your manager. You can follow up by saying even the best needs mentoring, and you always want to improve. So basically, this could work as an answer, but depending on the job, you might have a better shot with an answer like my example.
- published: 29 Jun 2014
- views: 4135932
Question answering
Question Answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically answer questions posed by humans in a natural language.
A QA implementation, usually a computer program, may construct its answers by querying a structured database of knowledge or information, usually a knowledge base. More commonly, QA systems can pull answers from an unstructured collection of natural language documents.
Some examples of natural language document collections used for QA systems include:
QA research attempts to deal with a wide range of question types including: fact, list, definition, How, Why, hypothetical, semantically constrained, and cross-lingual questions.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Question_answering
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Natural language
In neuropsychology, linguistics and the philosophy of language, a natural language or ordinary language is any language that develops naturally in humans through use and repetition (typically, in their first few years of life) without any conscious planning or premeditation of their own. Almost always, therefore, these are the languages human beings use to communicate with each other, whether by speech, signing, touch or writing. They are distinguished from constructed and formal languages such as those used to program computers or to study logic.
Defining natural language
Though the exact definition varies between scholars, natural language can broadly be defined in contrast to artificial or constructed languages (such as computer programming languages and international auxiliary languages) and to other communication systems in nature (such as bees' waggle dance). Definitions of "natural language" also usually state or imply that a "natural" language is one that any cognitively normal human infant is able to learn and whose development has been through use rather than by prescription. An unstandardized language such as African American Vernacular English, for example, is a natural language, whereas a standardized language such as Standard American English is, in part, prescribed.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Natural_language
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
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7:2921 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/ Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/ Offered by Coursera: https://www.coursera.org/ -
1:30:14Question Answering
Question AnsweringQuestion Answering
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product groups (Bing QnA team) to discuss the technical challenges faced in the real-world scenarios and highlight the research need. -
1:50:59Ben Bolte | Deep Language Modeling for Question Answering using Keras
Ben Bolte | Deep Language Modeling for Question Answering using KerasBen Bolte | Deep Language Modeling for Question Answering using Keras
PyData Carolinas 2016 Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models. Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better suited to this type of task because of their ability to capture higher-order syntax. Two papers, “Applying deep learning to answer selection: a study and an open task” (Feng et. al. 2015) and “LSTM-based deep learning models for non-factoid answer selection” (Tan et. al. 2016), are recent examples which have applied deep learning to question-answering tasks with good results. Feng et. al. used an in-house Java framework for their work, and Tan et. al. built their model entirely from Theano. This tutorial will demonstrate how to replicate the models used by each group using the popular open-source framework Keras, adding custom functions to include recent advances from the neural networks community. -
4:34NLQA Systems - Natural Language Questions Answering Systems
NLQA Systems - Natural Language Questions Answering SystemsNLQA Systems - Natural Language Questions Answering Systems
-
56:00Erik T. Mueller: Going Beyond Fact-Based Question Answering
Erik T. Mueller: Going Beyond Fact-Based Question AnsweringErik T. Mueller: Going Beyond Fact-Based Question Answering
Going Beyond Fact-Based Question Answering Erik T. Mueller http://xenia.media.mit.edu/~mueller/ To solve the AI problem, we need to develop systems that go beyond answering fact-based questions. Watson has been hugely successful at answering fact-based questions, but to solve hard AI tasks like passing science tests and understanding narratives, we need to go beyond simple facts. In this talk, I discuss how the systems I have most recently worked on have approached this problem. Watson for Healthcare answers Doctor's Dilemma medical competition questions, and WatsonPaths answers medical test preparation questions. These systems have achieved some success, but there is still a lot more to be done. Based on my experiences working on these systems, I discuss what I think the priorities should be going forward. First, to deal with the richness of human knowledge, we need to move... -
1:18:15Lecture 16: Dynamic Neural Networks for Question Answering
Lecture 16: Dynamic Neural Networks for Question AnsweringLecture 16: Dynamic Neural Networks for Question Answering
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"". Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images ------------------------------------------------------------------------------- Natural Language Processing with Deep Learning Instructors: - Chris Manning - Richard Socher Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component. For additional learning opportunities please visit: http://stanfordonline.stanford.edu/ -
1:05:32English Speaking Practice - Most Common Questions and Answers in English
English Speaking Practice - Most Common Questions and Answers in EnglishEnglish Speaking Practice - Most Common Questions and Answers in English
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle. ☞ Thanks for watching! ☞ Please share and like if you enjoyed the video :) thanks so much ♥ ─────────────────── ▶ Please subscribe to update new videos. Subscribe To Update New Lesson: https://www.youtube.com/channel/UCV1h_cBE0Drdx19qkTM0WNw?sub_confirmation=1 -
1:01:15Question Answering for Language and Vision
Question Answering for Language and Vision -
12:2508 common Interview question and answers - Job Interview Skills
08 common Interview question and answers - Job Interview Skills08 common Interview question and answers - Job Interview Skills
08 common Interview question and answers - Job Interview Skills 1. "Tell me a little about yourself." You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly. 2. "What are your strengths?" This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for. 3. "What are your weaknesses?" For this answer, you should display a weakness that can be seen as a strength. There are many types of answers that will work. Some answers will be good answers for certain jobs, while the same answer will be a bad answer for a different job. Select an answer that will work for the position you are applying for. 4. "Where do you see yourself in five years?" This question primarily depends on where you are in your career. A person with 5 years of experience will have different goals than a person with no work experience.This question is asked to see how serious a candidate is about his or her career. Some people might not know their goals, and some people might have goals of becoming rich and retiring early. Those are incorrect answers for this question. The type of answer you want to give is an ambitious answer that shows you really love your career. A good interviewer will read between the lines and find out if a person is going to be a hard worker or just a mediocre one. Being descriptive and shooting for a big goal is something interviewers want to hear. 5. "What do you know about our company?" A typical job interview question, asked to find out how much company research you have conducted, is "What do you know about this company?" Prepare in advance, and in a word, research, so you can provide relevant and current information about your prospective employer to the interviewer. 6. "Are you good at dealing with change?" Dealing with change is common in the work place. A simple yes will not be sufficient to impress the interviewer. This is another type of question where everyone will have similar answers. Of course everyone is going to claim being excellent dealing with change. You got to communicate that you are really good at dealing with change. 7. "Do you work well under pressure?" In most cases, the best answer to this question is answering yes. Working well under pressure is a good trait to have. However, I think if you answer that you work the same with pressure and without pressure, the interviewer will be more impressed. However, you will need to explain in words why this is better. 8. "How do you make important decisions?" There are many ways to answer this question, and if you have a reasonable method of making decisions, it will probably be sufficient. One answer I thought of included not being afraid of asking your manager. You can follow up by saying even the best needs mentoring, and you always want to improve. So basically, this could work as an answer, but depending on the job, you might have a better shot with an answer like my example. -
31:12QUESTION ANSWERING: PT. 1.
QUESTION ANSWERING: PT. 1.QUESTION ANSWERING: PT. 1.
Thanks so much for all the questions. You guys are my fav.
-
21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/ Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/ Offered by Coursera: https://www.coursera.org/
published: 30 Apr 2012 -
Question Answering
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product gro...
published: 22 Jun 2016 -
Ben Bolte | Deep Language Modeling for Question Answering using Keras
PyData Carolinas 2016 Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models. Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better...
published: 04 Oct 2016 -
NLQA Systems - Natural Language Questions Answering Systems
published: 22 Dec 2015 -
Erik T. Mueller: Going Beyond Fact-Based Question Answering
Going Beyond Fact-Based Question Answering Erik T. Mueller http://xenia.media.mit.edu/~mueller/ To solve the AI problem, we need to develop systems that go beyond answering fact-based questions. Watson has been hugely successful at answering fact-based questions, but to solve hard AI tasks like passing science tests and understanding narratives, we need to go beyond simple facts. In this talk, I discuss how the systems I have most recently worked on have approached this problem. Watson for Healthcare answers Doctor's Dilemma medical competition questions, and WatsonPaths answers medical test preparation questions. These systems have achieved some success, but there is still a lot more to be done. Based on my experiences working on these systems, I discuss what I think the priorities sho...
published: 11 Apr 2015 -
Lecture 16: Dynamic Neural Networks for Question Answering
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"". Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images ------------------------------------------------------------------------------- Natural Language Processing with Deep Learning Instructors: - Chris Manning - Richard Socher Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes h...
published: 03 Apr 2017 -
English Speaking Practice - Most Common Questions and Answers in English
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle. ☞ Thanks for watching! ☞ Please share and like if you enjoyed the video :) thanks so much ♥ ─────────────────── ▶ Please subscribe to update new videos. Subscribe To Update New Lesson: https://www.youtube.com/channel/UCV1h_cBE0Drdx19qkTM0WNw?sub_confirmation=1
published: 03 Sep 2016 -
-
08 common Interview question and answers - Job Interview Skills
08 common Interview question and answers - Job Interview Skills 1. "Tell me a little about yourself." You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly. 2. "What are your strengths?" This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for. 3. "What are your weaknesses?" For this answer,...
published: 29 Jun 2014 -
QUESTION ANSWERING: PT. 1.
Thanks so much for all the questions. You guys are my fav.
published: 05 Mar 2015
21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
- Order: Reorder
- Duration: 7:29
- Updated: 30 Apr 2012
- views: 7048
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online ...
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
https://wn.com/21_1_What_Is_Question_Answering_Nlp_Dan_Jurafsky_Chris_Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
- published: 30 Apr 2012
- views: 7048
Question Answering
- Order: Reorder
- Duration: 1:30:14
- Updated: 22 Jun 2016
- views: 395
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succi...
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product groups (Bing QnA team) to discuss the technical challenges faced in the real-world scenarios and highlight the research need.
https://wn.com/Question_Answering
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product groups (Bing QnA team) to discuss the technical challenges faced in the real-world scenarios and highlight the research need.
- published: 22 Jun 2016
- views: 395
Ben Bolte | Deep Language Modeling for Question Answering using Keras
- Order: Reorder
- Duration: 1:50:59
- Updated: 04 Oct 2016
- views: 2526
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number o...
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models.
Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better suited to this type of task because of their ability to capture higher-order syntax. Two papers, “Applying deep learning to answer selection: a study and an open task” (Feng et. al. 2015) and “LSTM-based deep learning models for non-factoid answer selection” (Tan et. al. 2016), are recent examples which have applied deep learning to question-answering tasks with good results.
Feng et. al. used an in-house Java framework for their work, and Tan et. al. built their model entirely from Theano. This tutorial will demonstrate how to replicate the models used by each group using the popular open-source framework Keras, adding custom functions to include recent advances from the neural networks community.
https://wn.com/Ben_Bolte_|_Deep_Language_Modeling_For_Question_Answering_Using_Keras
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models.
Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better suited to this type of task because of their ability to capture higher-order syntax. Two papers, “Applying deep learning to answer selection: a study and an open task” (Feng et. al. 2015) and “LSTM-based deep learning models for non-factoid answer selection” (Tan et. al. 2016), are recent examples which have applied deep learning to question-answering tasks with good results.
Feng et. al. used an in-house Java framework for their work, and Tan et. al. built their model entirely from Theano. This tutorial will demonstrate how to replicate the models used by each group using the popular open-source framework Keras, adding custom functions to include recent advances from the neural networks community.
- published: 04 Oct 2016
- views: 2526
NLQA Systems - Natural Language Questions Answering Systems
- Order: Reorder
- Duration: 4:34
- Updated: 22 Dec 2015
- views: 382
- published: 22 Dec 2015
- views: 382
Erik T. Mueller: Going Beyond Fact-Based Question Answering
- Order: Reorder
- Duration: 56:00
- Updated: 11 Apr 2015
- views: 1776
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go b...
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go beyond
answering fact-based questions. Watson has been hugely successful
at answering fact-based questions, but to solve hard AI tasks like
passing science tests and understanding narratives, we need to go
beyond simple facts. In this talk, I discuss how the systems I have
most recently worked on have approached this problem. Watson for
Healthcare answers Doctor's Dilemma medical competition questions,
and WatsonPaths answers medical test preparation questions. These
systems have achieved some success, but there is still a lot more
to be done. Based on my experiences working on these systems, I
discuss what I think the priorities should be going forward. First,
to deal with the richness of human knowledge, we need to move...
https://wn.com/Erik_T._Mueller_Going_Beyond_Fact_Based_Question_Answering
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go beyond
answering fact-based questions. Watson has been hugely successful
at answering fact-based questions, but to solve hard AI tasks like
passing science tests and understanding narratives, we need to go
beyond simple facts. In this talk, I discuss how the systems I have
most recently worked on have approached this problem. Watson for
Healthcare answers Doctor's Dilemma medical competition questions,
and WatsonPaths answers medical test preparation questions. These
systems have achieved some success, but there is still a lot more
to be done. Based on my experiences working on these systems, I
discuss what I think the priorities should be going forward. First,
to deal with the richness of human knowledge, we need to move...
- published: 11 Apr 2015
- views: 1776
Lecture 16: Dynamic Neural Networks for Question Answering
- Order: Reorder
- Duration: 1:18:15
- Updated: 03 Apr 2017
- views: 965
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks f...
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images
-------------------------------------------------------------------------------
Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
For additional learning opportunities please visit:
http://stanfordonline.stanford.edu/
https://wn.com/Lecture_16_Dynamic_Neural_Networks_For_Question_Answering
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images
-------------------------------------------------------------------------------
Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
For additional learning opportunities please visit:
http://stanfordonline.stanford.edu/
- published: 03 Apr 2017
- views: 965
English Speaking Practice - Most Common Questions and Answers in English
- Order: Reorder
- Duration: 1:05:32
- Updated: 03 Sep 2016
- views: 330964
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed ...
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed the video :) thanks so much ♥
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222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed the video :) thanks so much ♥
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- published: 03 Sep 2016
- views: 330964
Question Answering for Language and Vision
- Order: Reorder
- Duration: 1:01:15
- Updated: 24 Aug 2016
- views: 865
08 common Interview question and answers - Job Interview Skills
- Order: Reorder
- Duration: 12:25
- Updated: 29 Jun 2014
- views: 4135932
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communica...
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly.
2. "What are your strengths?"
This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for.
3. "What are your weaknesses?"
For this answer, you should display a weakness that can be seen as a strength. There are many types of answers that will work. Some answers will be good answers for certain jobs, while the same answer will be a bad answer for a different job. Select an answer that will work for the position you are applying for.
4. "Where do you see yourself in five years?"
This question primarily depends on where you are in your career. A person with 5 years of experience will have different goals than a person with no work experience.This question is asked to see how serious a candidate is about his or her career. Some people might not know their goals, and some people might have goals of becoming rich and retiring early. Those are incorrect answers for this question. The type of answer you want to give is an ambitious answer that shows you really love your career. A good interviewer will read between the lines and find out if a person is going to be a hard worker or just a mediocre one. Being descriptive and shooting for a big goal is something interviewers want to hear.
5. "What do you know about our company?"
A typical job interview question, asked to find out how much company research you have conducted, is "What do you know about this company?" Prepare in advance, and in a word, research, so you can provide relevant and current information about your prospective employer to the interviewer.
6. "Are you good at dealing with change?"
Dealing with change is common in the work place. A simple yes will not be sufficient to impress the interviewer. This is another type of question where everyone will have similar answers. Of course everyone is going to claim being excellent dealing with change. You got to communicate that you are really good at dealing with change.
7. "Do you work well under pressure?"
In most cases, the best answer to this question is answering yes. Working well under pressure is a good trait to have. However, I think if you answer that you work the same with pressure and without pressure, the interviewer will be more impressed. However, you will need to explain in words why this is better.
8. "How do you make important decisions?"
There are many ways to answer this question, and if you have a reasonable method of making decisions, it will probably be sufficient. One answer I thought of included not being afraid of asking your manager. You can follow up by saying even the best needs mentoring, and you always want to improve. So basically, this could work as an answer, but depending on the job, you might have a better shot with an answer like my example.
https://wn.com/08_Common_Interview_Question_And_Answers_Job_Interview_Skills
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly.
2. "What are your strengths?"
This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for.
3. "What are your weaknesses?"
For this answer, you should display a weakness that can be seen as a strength. There are many types of answers that will work. Some answers will be good answers for certain jobs, while the same answer will be a bad answer for a different job. Select an answer that will work for the position you are applying for.
4. "Where do you see yourself in five years?"
This question primarily depends on where you are in your career. A person with 5 years of experience will have different goals than a person with no work experience.This question is asked to see how serious a candidate is about his or her career. Some people might not know their goals, and some people might have goals of becoming rich and retiring early. Those are incorrect answers for this question. The type of answer you want to give is an ambitious answer that shows you really love your career. A good interviewer will read between the lines and find out if a person is going to be a hard worker or just a mediocre one. Being descriptive and shooting for a big goal is something interviewers want to hear.
5. "What do you know about our company?"
A typical job interview question, asked to find out how much company research you have conducted, is "What do you know about this company?" Prepare in advance, and in a word, research, so you can provide relevant and current information about your prospective employer to the interviewer.
6. "Are you good at dealing with change?"
Dealing with change is common in the work place. A simple yes will not be sufficient to impress the interviewer. This is another type of question where everyone will have similar answers. Of course everyone is going to claim being excellent dealing with change. You got to communicate that you are really good at dealing with change.
7. "Do you work well under pressure?"
In most cases, the best answer to this question is answering yes. Working well under pressure is a good trait to have. However, I think if you answer that you work the same with pressure and without pressure, the interviewer will be more impressed. However, you will need to explain in words why this is better.
8. "How do you make important decisions?"
There are many ways to answer this question, and if you have a reasonable method of making decisions, it will probably be sufficient. One answer I thought of included not being afraid of asking your manager. You can follow up by saying even the best needs mentoring, and you always want to improve. So basically, this could work as an answer, but depending on the job, you might have a better shot with an answer like my example.
- published: 29 Jun 2014
- views: 4135932
QUESTION ANSWERING: PT. 1.
- Order: Reorder
- Duration: 31:12
- Updated: 05 Mar 2015
- views: 2258
Thanks so much for all the questions. You guys are my fav.
Thanks so much for all the questions. You guys are my fav.
https://wn.com/Question_Answering_Pt._1.
-
21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/ Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/ Offered by Coursera: https://www.coursera.org/
published: 30 Apr 2012 -
Question Answering
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product gro...
published: 22 Jun 2016 -
Ben Bolte | Deep Language Modeling for Question Answering using Keras
PyData Carolinas 2016 Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models. Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better...
published: 04 Oct 2016 -
NLQA Systems - Natural Language Questions Answering Systems
published: 22 Dec 2015 -
Erik T. Mueller: Going Beyond Fact-Based Question Answering
Going Beyond Fact-Based Question Answering Erik T. Mueller http://xenia.media.mit.edu/~mueller/ To solve the AI problem, we need to develop systems that go beyond answering fact-based questions. Watson has been hugely successful at answering fact-based questions, but to solve hard AI tasks like passing science tests and understanding narratives, we need to go beyond simple facts. In this talk, I discuss how the systems I have most recently worked on have approached this problem. Watson for Healthcare answers Doctor's Dilemma medical competition questions, and WatsonPaths answers medical test preparation questions. These systems have achieved some success, but there is still a lot more to be done. Based on my experiences working on these systems, I discuss what I think the priorities sho...
published: 11 Apr 2015 -
Lecture 16: Dynamic Neural Networks for Question Answering
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"". Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images ------------------------------------------------------------------------------- Natural Language Processing with Deep Learning Instructors: - Chris Manning - Richard Socher Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes h...
published: 03 Apr 2017 -
English Speaking Practice - Most Common Questions and Answers in English
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle. ☞ Thanks for watching! ☞ Please share and like if you enjoyed the video :) thanks so much ♥ ─────────────────── ▶ Please subscribe to update new videos. Subscribe To Update New Lesson: https://www.youtube.com/channel/UCV1h_cBE0Drdx19qkTM0WNw?sub_confirmation=1
published: 03 Sep 2016 -
-
08 common Interview question and answers - Job Interview Skills
08 common Interview question and answers - Job Interview Skills 1. "Tell me a little about yourself." You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly. 2. "What are your strengths?" This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for. 3. "What are your weaknesses?" For this answer,...
published: 29 Jun 2014 -
QUESTION ANSWERING: PT. 1.
Thanks so much for all the questions. You guys are my fav.
published: 05 Mar 2015
21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
- Order: Reorder
- Duration: 7:29
- Updated: 30 Apr 2012
- views: 7048
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online ...
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
https://wn.com/21_1_What_Is_Question_Answering_Nlp_Dan_Jurafsky_Chris_Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
- published: 30 Apr 2012
- views: 7048
Question Answering
- Order: Reorder
- Duration: 1:30:14
- Updated: 22 Jun 2016
- views: 395
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succi...
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product groups (Bing QnA team) to discuss the technical challenges faced in the real-world scenarios and highlight the research need.
https://wn.com/Question_Answering
Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search engine queries. While both Bing and Google have incorporated more “semantics” to return direct answers to queries, QA is far from solved, and is becoming more important as natural language interaction becomes popular (e.g., Siri and Cortana). In this session, we invite experts from both academia and Microsoft to present recent technologies for improving QA. The topics include traditional IR approaches for QA, machine reading for knowledge acquisition and representation, and semantic parsing for answering questions using structured databases like Freebase or Satori. In addition, we invite product groups (Bing QnA team) to discuss the technical challenges faced in the real-world scenarios and highlight the research need.
- published: 22 Jun 2016
- views: 395
Ben Bolte | Deep Language Modeling for Question Answering using Keras
- Order: Reorder
- Duration: 1:50:59
- Updated: 04 Oct 2016
- views: 2526
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number o...
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models.
Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better suited to this type of task because of their ability to capture higher-order syntax. Two papers, “Applying deep learning to answer selection: a study and an open task” (Feng et. al. 2015) and “LSTM-based deep learning models for non-factoid answer selection” (Tan et. al. 2016), are recent examples which have applied deep learning to question-answering tasks with good results.
Feng et. al. used an in-house Java framework for their work, and Tan et. al. built their model entirely from Theano. This tutorial will demonstrate how to replicate the models used by each group using the popular open-source framework Keras, adding custom functions to include recent advances from the neural networks community.
https://wn.com/Ben_Bolte_|_Deep_Language_Modeling_For_Question_Answering_Using_Keras
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analysis, but have yet to make their way into mainstream usage in a number of popular fields. Recent advances in question-answering have come largely from creative applications of deep learning. In this tutorial, I will demonstrate how to modify the open-source framework Keras to build some of these models.
Question answering has received more focus as large search engines have basically mastered general information retrieval and are starting to cover more edge cases. Question answering happens to be one of those edge cases, because it could involve a lot of syntatic nuance that doesn’t get captured by standard information retrieval models, like BM-25 or LSI. Hypothetically, deep learning models are better suited to this type of task because of their ability to capture higher-order syntax. Two papers, “Applying deep learning to answer selection: a study and an open task” (Feng et. al. 2015) and “LSTM-based deep learning models for non-factoid answer selection” (Tan et. al. 2016), are recent examples which have applied deep learning to question-answering tasks with good results.
Feng et. al. used an in-house Java framework for their work, and Tan et. al. built their model entirely from Theano. This tutorial will demonstrate how to replicate the models used by each group using the popular open-source framework Keras, adding custom functions to include recent advances from the neural networks community.
- published: 04 Oct 2016
- views: 2526
NLQA Systems - Natural Language Questions Answering Systems
- Order: Reorder
- Duration: 4:34
- Updated: 22 Dec 2015
- views: 382
- published: 22 Dec 2015
- views: 382
Erik T. Mueller: Going Beyond Fact-Based Question Answering
- Order: Reorder
- Duration: 56:00
- Updated: 11 Apr 2015
- views: 1776
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go b...
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go beyond
answering fact-based questions. Watson has been hugely successful
at answering fact-based questions, but to solve hard AI tasks like
passing science tests and understanding narratives, we need to go
beyond simple facts. In this talk, I discuss how the systems I have
most recently worked on have approached this problem. Watson for
Healthcare answers Doctor's Dilemma medical competition questions,
and WatsonPaths answers medical test preparation questions. These
systems have achieved some success, but there is still a lot more
to be done. Based on my experiences working on these systems, I
discuss what I think the priorities should be going forward. First,
to deal with the richness of human knowledge, we need to move...
https://wn.com/Erik_T._Mueller_Going_Beyond_Fact_Based_Question_Answering
Going Beyond Fact-Based Question Answering
Erik T. Mueller
http://xenia.media.mit.edu/~mueller/
To solve the AI problem, we need to develop systems that go beyond
answering fact-based questions. Watson has been hugely successful
at answering fact-based questions, but to solve hard AI tasks like
passing science tests and understanding narratives, we need to go
beyond simple facts. In this talk, I discuss how the systems I have
most recently worked on have approached this problem. Watson for
Healthcare answers Doctor's Dilemma medical competition questions,
and WatsonPaths answers medical test preparation questions. These
systems have achieved some success, but there is still a lot more
to be done. Based on my experiences working on these systems, I
discuss what I think the priorities should be going forward. First,
to deal with the richness of human knowledge, we need to move...
- published: 11 Apr 2015
- views: 1776
Lecture 16: Dynamic Neural Networks for Question Answering
- Order: Reorder
- Duration: 1:18:15
- Updated: 03 Apr 2017
- views: 965
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks f...
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images
-------------------------------------------------------------------------------
Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
For additional learning opportunities please visit:
http://stanfordonline.stanford.edu/
https://wn.com/Lecture_16_Dynamic_Neural_Networks_For_Question_Answering
Lecture 16 addresses the question ""Can all NLP tasks be seen as question answering problems?"".
Key phrases: Coreference Resolution, Dynamic Memory Networks for Question Answering over Text and Images
-------------------------------------------------------------------------------
Natural Language Processing with Deep Learning
Instructors:
- Chris Manning
- Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.
For additional learning opportunities please visit:
http://stanfordonline.stanford.edu/
- published: 03 Apr 2017
- views: 965
English Speaking Practice - Most Common Questions and Answers in English
- Order: Reorder
- Duration: 1:05:32
- Updated: 03 Sep 2016
- views: 330964
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed ...
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed the video :) thanks so much ♥
───────────────────
▶ Please subscribe to update new videos.
Subscribe To Update New Lesson:
https://www.youtube.com/channel/UCV1h_cBE0Drdx19qkTM0WNw?sub_confirmation=1
https://wn.com/English_Speaking_Practice_Most_Common_Questions_And_Answers_In_English
222 Most Common Questions and Answers in English, Learn English Speaking Practice With Subtitle.
☞ Thanks for watching!
☞ Please share and like if you enjoyed the video :) thanks so much ♥
───────────────────
▶ Please subscribe to update new videos.
Subscribe To Update New Lesson:
https://www.youtube.com/channel/UCV1h_cBE0Drdx19qkTM0WNw?sub_confirmation=1
- published: 03 Sep 2016
- views: 330964
Question Answering for Language and Vision
- Order: Reorder
- Duration: 1:01:15
- Updated: 24 Aug 2016
- views: 865
08 common Interview question and answers - Job Interview Skills
- Order: Reorder
- Duration: 12:25
- Updated: 29 Jun 2014
- views: 4135932
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communica...
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly.
2. "What are your strengths?"
This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for.
3. "What are your weaknesses?"
For this answer, you should display a weakness that can be seen as a strength. There are many types of answers that will work. Some answers will be good answers for certain jobs, while the same answer will be a bad answer for a different job. Select an answer that will work for the position you are applying for.
4. "Where do you see yourself in five years?"
This question primarily depends on where you are in your career. A person with 5 years of experience will have different goals than a person with no work experience.This question is asked to see how serious a candidate is about his or her career. Some people might not know their goals, and some people might have goals of becoming rich and retiring early. Those are incorrect answers for this question. The type of answer you want to give is an ambitious answer that shows you really love your career. A good interviewer will read between the lines and find out if a person is going to be a hard worker or just a mediocre one. Being descriptive and shooting for a big goal is something interviewers want to hear.
5. "What do you know about our company?"
A typical job interview question, asked to find out how much company research you have conducted, is "What do you know about this company?" Prepare in advance, and in a word, research, so you can provide relevant and current information about your prospective employer to the interviewer.
6. "Are you good at dealing with change?"
Dealing with change is common in the work place. A simple yes will not be sufficient to impress the interviewer. This is another type of question where everyone will have similar answers. Of course everyone is going to claim being excellent dealing with change. You got to communicate that you are really good at dealing with change.
7. "Do you work well under pressure?"
In most cases, the best answer to this question is answering yes. Working well under pressure is a good trait to have. However, I think if you answer that you work the same with pressure and without pressure, the interviewer will be more impressed. However, you will need to explain in words why this is better.
8. "How do you make important decisions?"
There are many ways to answer this question, and if you have a reasonable method of making decisions, it will probably be sufficient. One answer I thought of included not being afraid of asking your manager. You can follow up by saying even the best needs mentoring, and you always want to improve. So basically, this could work as an answer, but depending on the job, you might have a better shot with an answer like my example.
https://wn.com/08_Common_Interview_Question_And_Answers_Job_Interview_Skills
08 common Interview question and answers - Job Interview Skills
1. "Tell me a little about yourself."
You should take this opportunity to show your communication skills by speaking clearly and concisely in an organized manner. Because there is no right or wrong answer for this question, it is important to appear friendly.
2. "What are your strengths?"
This is a popular interview question. They want to know what you think of yourself. Although this is a general question, there is a wrong and right answer. The wrong answer is a generic answer saying you are organized and friendly. Although it will not hurt you during the interview, it will certainly not help you either. Answer this question based on the type of job you are applying for.
3. "What are your weaknesses?"
For this answer, you should display a weakness that can be seen as a strength. There are many types of answers that will work. Some answers will be good answers for certain jobs, while the same answer will be a bad answer for a different job. Select an answer that will work for the position you are applying for.
4. "Where do you see yourself in five years?"
This question primarily depends on where you are in your career. A person with 5 years of experience will have different goals than a person with no work experience.This question is asked to see how serious a candidate is about his or her career. Some people might not know their goals, and some people might have goals of becoming rich and retiring early. Those are incorrect answers for this question. The type of answer you want to give is an ambitious answer that shows you really love your career. A good interviewer will read between the lines and find out if a person is going to be a hard worker or just a mediocre one. Being descriptive and shooting for a big goal is something interviewers want to hear.
5. "What do you know about our company?"
A typical job interview question, asked to find out how much company research you have conducted, is "What do you know about this company?" Prepare in advance, and in a word, research, so you can provide relevant and current information about your prospective employer to the interviewer.
6. "Are you good at dealing with change?"
Dealing with change is common in the work place. A simple yes will not be sufficient to impress the interviewer. This is another type of question where everyone will have similar answers. Of course everyone is going to claim being excellent dealing with change. You got to communicate that you are really good at dealing with change.
7. "Do you work well under pressure?"
In most cases, the best answer to this question is answering yes. Working well under pressure is a good trait to have. However, I think if you answer that you work the same with pressure and without pressure, the interviewer will be more impressed. However, you will need to explain in words why this is better.
8. "How do you make important decisions?"
There are many ways to answer this question, and if you have a reasonable method of making decisions, it will probably be sufficient. One answer I thought of included not being afraid of asking your manager. You can follow up by saying even the best needs mentoring, and you always want to improve. So basically, this could work as an answer, but depending on the job, you might have a better shot with an answer like my example.
- published: 29 Jun 2014
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QUESTION ANSWERING: PT. 1.
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- Updated: 05 Mar 2015
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Thanks so much for all the questions. You guys are my fav.
Thanks so much for all the questions. You guys are my fav.
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Questions & Answers (Part 4)
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Questions & Answers (Part 3)
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Question Answers
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Question & Answer session with Dwayne Lemon.
Question & Answer session with Dwayne Lemon.
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Questions & Answers (Part 4)
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- Updated: 14 Feb 2017
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- published: 14 Feb 2017
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Weekly Updates, Question & Answers.
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Questions & Answers (Part 3)
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- Updated: 27 Oct 2016
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Questions & Answers 252
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21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
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21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
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Question Answering
Natural-language question answering (QA) has clear practical and scientific values, such a...
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Ben Bolte | Deep Language Modeling for Question Answering using Keras
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analys...
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Erik T. Mueller: Going Beyond Fact-Based Question Answering
Going Beyond Fact-Based Question Answering
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Lecture 16: Dynamic Neural Networks for Question Answering
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English Speaking Practice - Most Common Questions and Answers in English
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Question Answering for Language and Vision
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08 common Interview question and answers - Job Interview Skills
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08 common Interview question and answers - Job Interview Skills
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QUESTION ANSWERING: PT. 1.
Thanks so much for all the questions. You guys are my fav.
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21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
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21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning
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Question Answering
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Ben Bolte | Deep Language Modeling for Question Answering using Keras
PyData Carolinas 2016
Neural network models have revolutionized many areas of data analys...
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Ben Bolte | Deep Language Modeling for Question Answering using Keras
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NLQA Systems - Natural Language Questions Answering Systems
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56:00
Erik T. Mueller: Going Beyond Fact-Based Question Answering
Going Beyond Fact-Based Question Answering
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http://xenia.media.mit.edu/~m...
published: 11 Apr 2015
Erik T. Mueller: Going Beyond Fact-Based Question Answering
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Lecture 16: Dynamic Neural Networks for Question Answering
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Lecture 16: Dynamic Neural Networks for Question Answering
Lecture 16: Dynamic Neural Networks for Question Answering
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English Speaking Practice - Most Common Questions and Answers in English
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English Speaking Practice - Most Common Questions and Answers in English
English Speaking Practice - Most Common Questions and Answers in English
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Question Answering for Language and Vision
Richard Socher - MetaMind (A Salesforce Company)
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Question Answering for Language and Vision
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08 common Interview question and answers - Job Interview Skills
08 common Interview question and answers - Job Interview Skills
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08 common Interview question and answers - Job Interview Skills
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31:12
QUESTION ANSWERING: PT. 1.
Thanks so much for all the questions. You guys are my fav.
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