Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

机器学习相关教程

Set up deep learning environment in a single command line.

中文 Python 笔记

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

Deep Reinforcement Learning for Keras.

A course in reinforcement learning in the wild

Lightweight library to build and train neural networks in Theano

Introduction to Deep Neural Networks with Keras and Tensorflow

Neural network visualization toolkit for keras

Deep learning driven jazz generation using Keras & Theano!

An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

This is now the official location of the Merlin project.

DL course co-developed by YSDA, HSE and Skoltech

Keras implementation of BERT with pre-trained weights

💻 Make machines learn so that you don't have to struggle to program them; The ultimate list

Gesture recognition via CNN. Implemented in Keras + Tensorflow/Theano + OpenCV

RNN-based generative models for speech.

GPU-accelerated Deep Learning on Windows 10 native

Keras package for region-based convolutional neural networks (RCNNs)

Neural Machine Translation with Keras

A deep neural network for face alignment

A bidirectional recurrent neural network model with attention mechanism for restoring missing punctuation in unsegmented text

Text Classification Library in Keras

Deep Convolutional Neural Networks for Musical Source Separation

GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to adress parameter and model uncertainties.

Reimplementation of DRAW

Implementation of Dynamic memory networks by Kumar et al. http://arxiv.org/abs/1506.07285

The data is the future of oil, digging the potential value of the data is very meaningful. This library records my road of machine learning study.