Various deep learning algorithms implemented in TensorFlow.
This is a tutorial for image classification using MNIST. 4 different implementation are provided in MNIST/mymodels, together with simple k-NN neighbor.
- mlp_notf.py
- Multiple Layer Perceptron (MLP) without TensorFlow
- mlp.py
- MLP with Tensorflow
- ???
- Stacked Denoising Autoencoder + MLP
- cnn.py
- Convolutional neural network (CNN)
The accuracy of those 4 (+1) programs can be evaluated on a same interface here.
Classification of CIFAR-10 by CNN and various preprocessing.
- Data Augmentation
- Global Contrast Normalization (GCN)
- ZCA Whitening
Sentiment analysis of IMDb (movie review dataset) by Recurrent Neural Network (RNN).
English-Japanese machine translation by Long Short-Term Memory (LSTM), trained by Tanaka Corpus.
Image caption generation of MS COCO (Microsoft Common Objects in Context) by CNN + LSTM + Attention model.
Assume you are using anaconda3 environment.
pip install tensorflow-gpu
pip install keras