- This is the 2020 version. For previous year' course materials, go to this branch
- Lecture and seminar materials for each week are in ./week* folders, see README.md for materials and instructions
- YSDA homework deadlines will be listed in Anytask (read more).
- Any technical issues, ideas, bugs in course materials, contribution ideas - add an issue
- Installing libraries and troubleshooting: this thread.
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week01 Word Embeddings
- Lecture: Word embeddings. Distributional semantics. Count-based (pre-neural) methods. Word2Vec: learn vectors. GloVe: count, then learn. Evaluation: intrinsic vs extrinsic. Analysis and Interpretability. Interactive lecture materials and more.
- Seminar: Playing with word and sentence embeddings.
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week02 Text Classification
- Lecture: Text classification: introduction and datasets. General framework: feature extractor + classifier. Classical approaches: Naive Bayes, MaxEnt (Logistic Regression), SVM. Neural Networks: General View, Convolutional Models, Recurrent Models. Analysis and Interpretability. Interactive lecture materials and more.
- Seminar: TBA
More TBA
Course materials and teaching performed by
- Elena Voita - course admin, lectures, seminars, homeworks
- Boris Kovarsky - lectures, seminars, homeworks
- David Talbot - lectures, seminars, homeworks
- Sergey Gubanov - lectures, seminars, homeworks
- Just Heuristic - lectures, seminars, homeworks