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adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

applied-deep-learning-resources

A collection of research articles, blog posts, slides and code snippets about deep learning in applied settings.

async-rl-tensorflow

Asynchronous Methods for Deep Reinforcement Learning

awesome-public-datasets

An awesome list of high-quality open datasets in public domains (on-going).

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

ba-dls-deepspeech

bnlstm

Batch normalized LSTM for tensorflow

brainstorm

Fast, flexible and fun neural networks.

cc-mrjob

Demonstration of using Python to process the Common Crawl dataset with the mrjob framework

chainer

A flexible framework of neural networks for deep learning

cntk

Computational Network Toolkit (CNTK)

codebase

Repository of some utils

cs224u

Code for Stanford CS224u

datavizweb.github.io

Blog

deep-learning-keras-euroscipy2016

# Deep Learning with Keras

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deepspeech.mxnet

A MXNet implementation of Baidu's DeepSpeech architecture

easy_seq2seq

An easy to use seq2seq model based on tensorflow's seq2seq

faiss

A library for efficient similarity search and clustering of dense vectors.

fast-wavenet

Efficient implementation of Wavenet generation.

fasttext

Library for fast text representation and classification.

g2p-tf

Sequence to Sequence based grapheme to phoneme using tensorflow

genadv_tutorial

TensorFlow tutorial on Generative Adversarial Models

gym

A toolkit for developing and comparing reinforcement learning algorithms.

home

irstlm

jekyll-now

Build a Jekyll blog in minutes, without touching the command line.

justext

Heuristic based boilerplate removal tool

kaldi-io-for-python

Python functions for reading kaldi data formats. Useful for rapid prototyping with python.

keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on MXNet, Theano or TensorFlow.