monkey's repositories
tensor2tensor
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
conv_seq2seq
A tensorflow implementation of Fairseq Convolutional Sequence to Sequence Learning(Gehring et al. 2017)
DCGAN-tensorflow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
DeepLearning-Lab
some code about deep learning
DeepRL-Agents
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
gStore
gStore v2.0 - a graph based RDF triple store.
hub
A library for transfer learning by reusing parts of TensorFlow models.
kmeans
A CUDA implementation of the k-means clustering algorithm
KNET
Neural Entity Typing with Knowledge Attention
leveldb
LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
LoveIt
🚀A clean, elegant but advanced blog theme for Hugo
models
Models and examples built with TensorFlow
mps
A multi-pass sieve for coreference resolution in Python
MSongsDB
Code for the Million Song Dataset, the dataset contains metadata and audio analysis for a million tracks, a collaboration between The Echo Nest and LabROSA. See website for details.
nmt
TensorFlow Neural Machine Translation Tutorial
pointer-networks
TensorFlow implementation of Pointer Networks, modified to use a threshold (or hardmax) pointer instead of a softmax pointer.
RankGan-NIPS2017
Tensorflow implementation of RankGan (Adversarial Ranking for Language Generation)
SeqGAN
Implementation of Sequence Generative Adversarial Nets with Policy Gradient
stanford-corenlp
Python wrapper for Stanford CoreNLP.
tensorflow
Computation using data flow graphs for scalable machine learning
tensorflow_practice
tensorflow实战练习，包括强化学习、推荐系统、nlp等
tf_rnn
Recursive Neural Networks implemented with Tensorflow
transformer
A TensorFlow Implementation of the Transformer: Attention Is All You Need
zhihu
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.