Assignment-Guidelines-and-Solutions
Lecture-1-Intro-to-NLP-and-Deep-Learning
Lecture-10-Neural-Machine-Translation-and-Models-with-Attention
Lecture-11-GRUs-and-Further-Topics-in-NMT
Lecture-12-End-to-End-Model-Speech-Processing
Lecture-13-Convolutional-Neural-Networks
Lecture-14-Tree-Recursive-Neural-Networks-and-Constituency-Parsing
Lecture-15-Coreference-Resolution
Lecture-16-Dynamic-Neural-Networks-for-Question-Answering
Lecture-17-Issues-in-NLP-and-Possible-Architectures-in-NLP
Lecture-18-Tackling-the-limits-of-Deep-Learning-for-NLP
cs224n-2017-lecture18-highlight.pdf
cs224n-2017-lecture18.pdf
neural-turing-machine.pdf
Lecture-2-Word-Vector-Representations
Lecture-3-Advanced-Word-Vector-Representations
Lecture-4-Word-Window-Classification-and-Neural-Networks
Lecture-5-Backpropagation-and-Project-Advice
Lecture-6-Introduction-to-TensorFlow
Lecture-7-Dependency-Parsing
Lecture-8-Recurrent-Neural-Nets-and-Language-Models
Lecture-9-Machine-Translation-and-Advanced-Recurrent-LSTMs-GSU
Review-Session-Midterm-Review
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