Course pages 2017–18
Deep learning for natural language processing
Lectures
- 1. Introduction to Neural Networks for NLP (Clark) [PDF]
- 2. Feedforward Neural Networks for NLP (Clark) [PDF]
- 3. Training and Optimization (Clark) [PDF]
- 4. Word Embeddings (Hill) [PDF]
- 5. Recurrent Neural Networks (Hill) [PDF]
- 7. Tensorflow (Clark) [PDF]
- 8. Long Short Term Memory (Hill) [PDF]
- 9. Conditional Language Modeling (Dyer) [PDF]
- 10. Better Conditional Language Modeling (Dyer) [PDF]
- 11. Machine Comprehension (Grefenstette) [PDF]
- 12. Convolutional Neural Networks (Hill) [PDF]
- 13. Sentence Representations (Grefenstette) [PDF]
- 13. Sentence Representations (Hill) [PDF]
- 14. Image Captioning (Clark) [PDF]
- 15. Situated Language Learning (Hill) [PDF]
Reading List
- The Deep Learning textbook
- A Primer on Neural Network Models for Natural Language Processing, Yoav Goldberg