ds-ga fall lecture

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1. 1▶DS-GA 1011 (Fall 2021) Lecture 1 - Course Logistics & Machine Learning BasicsDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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2. 2▶DS-GA 1011 (Fall 2021) Lecture 2 - Text ClassificationDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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3. 3▶DS-GA 1011 (Fall 2021) Lecture 3 - n-gram Language ModelingDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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4. 4▶DS-GA 1011 (Fall 2021) Lecture 4 - recurrent neural network language models and perplexityDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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5. 5▶DS-GA 1011 (Fall 2021) Lecture 5 - vanishing gradient and grated recurrent unitsDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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6. 6▶DS-GA 1011 (Fall 2021) Lecture 6 - attention and masked language modelingDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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7. 7▶DS-GA 1011 (Fall 2021) Lecture 7 - Semi-supervised learning and transfer learning in NLPDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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8. 8▶DS-GA 1011 Lecture 8 - Conditional language modelingDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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9. 9▶DS-GA 1011 (Fall 2021) - Lecture 9 - Matrix factorization and language modelingDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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10. 10▶DS-GA 1011 (Fall 2021) - Lecture 10 - Probabilistic PCA and latent-variable sequence modelingDS-GA 1011 (Fall 2021) Deep Learning for Natural Language ProcessingNotes
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