Stanford CS224N NLP with Deep Learning Winter 2021 Lecture 2 – Neural Classifiers

Stanford CS224N NLP with Deep Learning Winter 2021 Lecture 2 – Neural Classifiers

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Stanford CS224N NLP with Deep Learning Winter 2021 Lecture 2 – Neural Classifiers
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To learn more about Stanford's professional and graduate programs in artificial intelligence, visit: https://stanford.io/2ZB72nu

Lecture 2: Word vectors, word meanings and neural network classifications
1. Course organization (2 min.)
2. Look at word vectors and word2vec (13 minutes)
3. Can we capture the essence of word meaning more effectively by counting? (8m)
4. The GloVe model of word vectors (8 min)
5. Evaluating word vectors (14 min)
6. Word senses (8 min.)
7. Review of Classification and How Neural Nets Differ (8 minutes)
8. Introducing Neural Networks (14 min.)

For more information about this course, visit: https://online.stanford.edu/courses/cs224n-natural-lingual-processing-deep-learning
To follow the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224n/

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

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