High-level plan for problem sets(00:07:02 - 01:21:52) - Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 1 – Introduction and Word Vectors

High-level plan for problem sets(00:07:02 - 01:21:52)
Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 1 – Introduction and Word Vectors

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3CORGu1

This lecture covers many topics within Natural Language Understanding, including:
-The Course (10 min)
-Human language and word meaning (15 min)
-Wordzvec introduc...
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3CORGu1

This lecture covers many topics within Natural Language Understanding, including:
-The Course (10 min)
-Human language and word meaning (15 min)
-Wordzvec introductions (15 min)
-WordZvec objective function gradients (25 min)
-Optimization basics (5 min)
-Looking at word vectors (10 min for less)

Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)

To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224n/index.html#schedule

0:00 Introduction
00:41 Welcome
01:31 Overview for the lecture
01:56 Lecture Plan & Overview
02:02 Course logistics in brief
02:52 What do we hope to teach in this course?
05:39 Course work and grading policy
07:02 High-level plan for problem sets

#ChristopherManning #naturallanguageprocessing #deeplearning

#Stanford Artificial Intelligence Laboratory #Artificial Intelligence #Machine Learning #Deep Learning #Stanford #Computer Science

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