This repository is the code companion to my book "Fundamentals of Deep Learning." All algorithms are implemented in Tensorflow, Google's new machine intelligence library.
- Logistic Regression (Nikhil)
- Multilayer Perceptron (Nikhil)
- Convolutional Network (Nikhil)
- Neural Style (Anish)
- Autoencoder (Hassan)
- Denoising Autoencoder (Hassan)
- Convolutional Autoencoder (Hassan)
- RNN (Nikhil)
- LSTM Network (Nikhil)
- GRU Network (Nikhil)
- LSTM + Attention (Nikhil)
- RCNN (Nikhil)
- Memory Networks (Nikhil)
- Pointer Networks
- Neural Turing Machines
- Neural Programmer
- DQN
- LSTM-DQN
- Deep Convolutional Inverse Graphics Network
- Highway Networks
- Deep Residual Networks
- Word2Vec (Nikhil)
- Skip-gram/CBoW
- GloVe (Nikhil)
- Skip-thought Vectors (Nikhil)
- MLP + Momentum
- MLP + RMSProp
- MLP + ADAM
- MLP + FTRL
- MLP + ADADELTA