Supervised Learning
My first project below is my implementation of chapter 10: sequence modelling of "Deep Learning" Goodfellow, Bengio & Courville. As well as a Neural Turing Machine, Graves et al. Attention Mechanisms, such as location-based, Bahdanau, self and multi-head. Finally a Transformer, Vaswani et al.
My implementation of Goodfellow, Bengio & Courville, Deep Learning. Plus many other sequence models.
Sequence Modelling
- A1.
Simple RNN - A2.
Deep RNN - A2.
Deep RNN - A3.
GRU - A4.
LSTM - B1.
Dilated RNN - B2.
Wavenet - C1.
Neural Turing Machine - C2.
Attention - C3.
Transformer - May Add:
Pointer Network, SNAIL, Self-Attention GAN
- This project contains the landmark algorithms in sequence modelling in ML. I start off with the simpler, older algorithms and progress to the current state of the art algorithms. Implemented in PyTorch.