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Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 2 - Neural Classifiers
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Stanford CS224N: Natural Language Processing with Deep Learning | Winter 2021 - Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 2 - Neural Classifiers

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  • 31.5 hours of video
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For more information about Stanford's Artificial Intelligence professional and graduate programs visit: https://stanford.io/2ZB72nu Lecture 2: Word Vectors, Word Senses, and Neural Network Classifiers 1. Course organization (2 mins) 2. Finish looking at word vectors and word2vec (13 mins) 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 mins) 6. Word senses (8 mins) 7. Review of classification and how neural nets differ (8 mins) 8. Introducing neural networks (14 mins) To learn more about this course visit: https://online.stanford.edu/courses/cs224n-natural-language-processing-deep-learning To follow along with the course schedule and syllabus visit: http://web.stanford.edu/class/cs224n/ Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Director, Stanford Artificial Intelligence Laboratory (SAIL)

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