| 1 |
Introduction |
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| 2 |
Text classification: Logistic regression |
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Logistic Regression |
| 3 |
Text classification: Feed-forward neural networks |
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Minigrad; Simple NN Classifier |
| 4 |
Word embeddings: Latent semantic analysis |
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| 5 |
Word embeddings: Word2vec |
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| 6 |
Language modeling: n-gram language models |
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Statistical LM |
| 7 |
Language modeling: Neural network language models |
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| 8 |
Statistical machine translation |
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| 9 |
Seq2seq models |
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| 10 |
Natural language generation |
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| 11 |
Contextualized word embeddings: Elmo |
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| 12 |
Transformers and BERT |
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| 13 |
Efficient Fine-tuning |
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| 14 |
In-Context Learning |
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| 15 |
NLP Applications: NLP in medicine |
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