* [[https://github.com/fchollet/keras][Keras]] example codes

** Dependencies

I recommend using anaconda3

- python libraries
  - Keras
  - tensorflow or theano
  - pydot_ng
  - matplotllib
  - daft (only ~tutorial~ )
  - gensim (only save and load word embeddings)

- software
  - graphviz


** Contents

*** Keras 1

- Image
  - ~CNN_MNIST~
  - ~variational auto encoder for CIFAR10~
  - ~Gumbel-softmax with variational auto encoder for MNIST~
  - ~residual CIFAR10~

- Text
  - ~encoder-decoder~
  - ~Skip-Gram~ : not hieraltical softmax and negative sampling

- Tutorial
  - ~keras_tutorial~ : for Machine Learning seminar at Tsukuba (note: 7MB notebook and ja only)


*** Keras 2

- ~autoencoder~
- ~MLP_MNIST~
- ~CNN_CIFAR10~

- ~CBoW~ : Normal softmax
- ~RNN_binary_classification~
- ~NNLM~
- ~SCRNLM~ : Structurally Constrained Recurrent Nets Language Model
- ~fastText~ : Bi-gram features and softmax
- ~Skip-Gram&NG~ : Skip-gram with negative sampling
- ~prodLDA~ : Product of experts model's LDA based on VAE
- ~sklearn_MLP_MNIST~: Sklearn API example for parameter search on MNIST classification