References
Artificial Neural Networks (ANNs) and Deep Learning
NYU Center for Data Science:
Natural Language Processing
Stanford University
| Course | Material |
| CS224N: Natural Language Processing with Deep Learning | |
| Speech and Language Processing | |
| GloVe: Global Vectors for Word Representation | |
| Learning Visual N-Grams from Web Data | |
Stanford University School of Engineering
| Lecture | Subject | |
| 2 | Word Vector Representations: word2vec | |
| 3 | GloVe: Global Vectors for Word Representation | |
| 4 | Word Window Classification and Neural Networks | |
| 5 | Backpropagation and Project Advice | |
| 6 | Dependency Parsing | |
| 7 | Introduction to TensorFlow | |
| 8 | Recurrent Neural Networks and Language Models | |
| 9 | Machine Translation and Advanced Recurrent LSTMs and GRUs | |
| Review Session | Midterm Review | |
| 10 | Neural Machine Translation and Models with Attention | |
| 11 | Gated Recurrent Units and Further Topics in NMT | |
| 12 | End-to-End Models for Speech Processing | |
| 13 | Convolutional Neural Networks | |
| 14 | Tree Recursive Neural Networks and Constituency Parsing | |
| 15 | Coreference Resolution | |
| 16 | Dynamic Neural Networks for Question Answering | |
| 17 | Issues in NLP and Possible Architectures for NLP | |
| 18 | Tackling the Limits of Deep Learning for NLP | |