| Jan 22 |
Introduction |
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NLP (circa 2001) |
| Jan 24 |
" |
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Warming up! |
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Text classification, data basics, and the perceptron |
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| Jan 29 |
" |
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Neural networks basics |
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Back-prop, Deep Averaging Networks, Gradient Checks (briefly), Gradient Checks (in details) |
| Jan 31 |
" |
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| Feb 05 |
Learning from raw data |
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Word embeddings |
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w2v explained, Levy2014, word2vec, word2vec phrases, Hill2016, Turney2010 |
| Feb 07 |
" |
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| Feb 12 |
" |
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Language modeling |
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Collins: LM, Smoothing, More about smoothing |
| Feb 14 |
" |
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| Feb 19 |
Tokenization |
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Mielke2021, BPE notebook, HF summary |
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Neural LMs and Transformers |
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Annotated Transformer, Illustrated Transformer, Vaswani2017 |
| Feb 21 |
" |
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| Feb 26 |
No class ⛷️ |
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| Feb 28 |
Neural LMs and Transformers |
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| Mar 04 |
" |
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Decoding LMs |
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Scaling up to LLMs |
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| Mar 06 |
" |
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| Mar 11 |
Masked LMs |
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Raw data recap |
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Prototypical NLP tasks |
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| Mar 13 |
" |
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| Mar 18 |
" |
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| Mar 20 |
" |
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| Mar 25 |
" |
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| Mar 27 |
" |
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| Apr 01 |
No class ⛱️ |
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| Apr 03 |
No class 🏖️ |
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| Apr 08 |
" |
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Aligning LLMs |
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| Apr 10 |
" |
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| Apr 15 |
" |
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| Apr 17 |
Guest lecture: Orhan Firat (Google) – LLMs at Google |
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| Apr 22 |
Aligning LLMs |
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| Apr 24 |
Guest lecture: Joel Tetreault (Dataminr) – History of NLP |
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| Apr 29 |
Working with LLMs: Prompting |
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| May 01 |
" |
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Encoder-decoder Pre-training |
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| May 06 |
Recurrent neural networks |
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