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• DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing

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• DS-GA 1011 (Fall 2021) Lecture 1 - Course Logistics & Machine Learning Basics

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) Lecture 2 - Text Classification

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) Lecture 3 - n-gram Language Modeling

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) Lecture 4 - recurrent neural network language models and perplexity

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) Lecture 5 - vanishing gradient and grated recurrent units

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) Lecture 6 - attention and masked language modeling

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) Lecture 7 - Semi-supervised learning and transfer learning in NLP

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 Lecture 8 - Conditional language modeling

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) - Lecture 9 - Matrix factorization and language modeling

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

• DS-GA 1011 (Fall 2021) - Lecture 10 - Probabilistic PCA and latent-variable sequence modeling

  DS-GA 1011 (Fall 2021) Deep Learning for Natural Language Processing · 2021-12-31

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