1、tensorflow/tensorflow

　　Introduction

　　Computation using data flow graphs for scalable machine learning

　　GitHub：https://github.com/tensorflow/tensorflow

2、BVLC/caffe

　　Introduction

　　Caffe: a fast open framework for deep learning.

　　GitHub：https://github.com/BVLC/caffe

3、ZuzooVn/machine-learning-for-software-engineers

　　Introduction

　　A complete daily plan for studying to become a machine learning engineer.

　　GitHub：https://github.com/ZuzooVn/machine-learning-for-software-engineers

4、fchollet/keras

　　Introduction

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

　　GitHub：https://github.com/fchollet/keras

5、songrotek/Deep-Learning-Papers-Reading-Roadmap

　　Introduction

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

　　GitHub：https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap

6、Microsoft/CNTK

　　Introduction

　　Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

　　GitHub：https://github.com/Microsoft/CNTK

7、aymericdamien/TensorFlow-Examples

　　Introduction

　　TensorFlow Tutorial and Examples for beginners

　　GitHub：https://github.com/aymericdamien/TensorFlow-Examples

8、terryum/awesome-deep-learning-papers

　　Introduction

　　The most cited deep learning papers

　　GitHub：https://github.com/terryum/awesome-deep-learning-papers

9、dmlc/mxnet

　　Introduction

　　Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Java and more

　　GitHub：https://github.com/dmlc/mxnet

10、donnemartin/data-science-ipython-notebooks

　　Introduction

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

　　GitHub：https://github.com/donnemartin/data-science-ipython-notebooks

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