点上方蓝字计算机视觉联盟获取更多干货
在右上方 ··· 设为星标 ★,与你不见不散
AI博士笔记系列推荐:
Deepnet
Deeppy
JavaNN
hebel
Mocha.jl
OpenDL
cuDNN
MGL
Knet.jl
Nvidia DIGITS - a web app based on Caffe
Neon - Python based Deep Learning Framework
Keras - Theano based Deep Learning Library
Chainer - A flexible framework of neural networks for deep learning
RNNLM Toolkit
RNNLIB - A recurrent neural network library
char-rnn
MatConvNet: CNNs for MATLAB
Minerva - a fast and flexible tool for deep learning on multi-GPU
Brainstorm - Fast, flexible and fun neural networks.
Tensorflow - Open source software library for numerical computation using data flow graphs
Caffe
Torch7
Theano
cuda-convnet
convetjs
Ccv
NuPIC
DeepLearning4J
Brain
DeepLearnToolbox
DMTK - Microsoft Distributed Machine Learning Tookit
Scikit Flow - Simplified interface for TensorFlow (mimicking Scikit Learn)
MXnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning framework
Veles - Samsung Distributed machine learning platform
Marvin - A Minimalist GPU-only N-Dimensional ConvNets Framework
Apache SINGA - A General Distributed Deep Learning Platform
DSSTNE - Amazon's library for building Deep Learning models
SyntaxNet - Google's syntactic parser - A TensorFlow dependency library
mlpack - A scalable Machine Learning library
Torchnet - Torch based Deep Learning Library
Paddle - PArallel Distributed Deep LEarning by Baidu
NeuPy - Theano based Python library for ANN and Deep Learning
Lasagne - a lightweight library to build and train neural networks in Theano
nolearn - wrappers and abstractions around existing neural network libraries, most notably Lasagne
Sonnet - a library for constructing neural networks by Google's DeepMind
PyTorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
CNTK - Microsoft Cognitive Toolkit
Serpent.AI - Game agent framework: Use any video game as a deep learning sandbox
Caffe2 - A New Lightweight, Modular, and Scalable Deep Learning Framework
deeplearn.js - Hardware-accelerated deep learning and linear algebra (NumPy) library for the web
声明:本文来源于联盟学习笔记
联盟学术交流群
本文分享自微信公众号 - 算法猿的成长(AI_Developer)。
如有侵权,请联系 [email protected] 删除。
本文参与“OSC源创计划”,欢迎正在阅读的你也加入,一起分享。