YSDA course in Natural Language Processing
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- This is the 2019 version. For previous year' course materials, go to this branch
- Lecture and seminar materials for each week are in ./week* folders
- 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.
- Lecture: Word embeddings. Distributional semantics, LSA, Word2Vec, GloVe. Why and when we need them.
- Seminar: Playing with word and sentence embeddings.
week02 Text classification
- Lecture: Text classification. Classical approaches for text representation: BOW, TF-IDF. Neural approaches: embeddings, convolutions, RNNs
- Seminar: Salary prediction with convolutional neural networks; explaining network predictions.
week03 Language Models
- Lecture: Language models: N-gram and neural approaches; visualizing trained models
- Seminar: Generating ArXiv papers with language models
- Lecture: Seq2seq: encoder-decoder framework. Attention: Bahdanau model. Self-attention, Transformer. Analysis of attention heads in Transformer.
- Seminar: Machine translation of hotel and hostel descriptions
- Lecture: Expectation-Maximization and Hidden Markov Models
- Seminar: Implementing expectation maximization
week06 Machine Translation
- Lecture: Word Alignment Models, Noisy Channel, Machine Translation.
- Seminar: Introduction to word alignment assignment.
Contributors & course staff
Course materials and teaching performed by