Taking together Stanford CS224n course
Track your progress here
Course page: link
YouTube Videos: link
How to submit homework:
- Fork repository
- Commit finished assignment and push it
- Make a pull request
- Wait until 1 or 2 reviewers approve your solution
- Merge your pull request
- Video lecture
- Additional materials:
- Video lecture
- Enriching Word Vectors with Subword Information
- Additional materials:
- Optional materials:
- Video lecture
- Matrix calculus review, Differential calculus review
- Derivatives, Backprop, and Vectorization
- Learning representations by back-propagating errors
- CS231n notes on network architectures and backprop
- Additional materials:
- Optional materials:
- NLP (Almost) from Scratch - optional, but highly recommended
- Video lecture
- Lecture notes
- Sequence modeling: Recurrent and Recursive Neural Networks
- On the difficulty of training Recurrent Neural Networks
- Vanishing gradient Jupyter notebook
- Understanding LSTM
Assignment 1
deadline: 16/07/21
Assignment 2 explanation
Assignment 2 code
deadline: 30/07/21
Assignment 3 explanation (Skipping)
Assignment 3 code (Skipping)
deadline: 7/09/21
- Adversarial attacks on NLP models (https://arxiv.org/pdf/1911.03677.pdf)
- NLP models (BERT, RoBERT, ALBERT, etc.) in continual or multitask learning setting