Deep Learning with Machine Learning


Published: 09 Oct 2015

Deep Learning Tutorials


Deep learning

VGG Convolutional Neural Networks Practical

Hacker’s guide to Neural Networks

Deep Learning Tutorials

Deep Learning in a Nutshell: Core Concepts

Deep Learning in a Nutshell: History and Training

A Deep Learning Tutorial: From Perceptrons to Deep Networks

Deep Neural Networks (with Python code)

Three Classes of Deep Learning Architectures and Their Applications: A Tutorial Survey

Stanford Unsupervised Feature Learning and Deep Learning Tutorial: UFLDL Tutorial

The Unreasonable Effectiveness of Deep Learning (LeCun)

Deep learning from the bottom up

Introduction to Deep Learning with Python (By Alec Radford. Theano)

New to deep learning? Here are 4 easy lessons from Google

Deep Learning 101

Neural Networks Demystified

Deep Learning SIMPLIFIED

A ‘Brief’ History of Neural Nets and Deep Learning

Deep Neural Networks — An Overview

A Tutorial on Deep Neural Networks for Intelligent Systems

Deep Learning for Computer Vision – Introduction to Convolution Neural Networks

BI Lab Deep Learning Tutorial

Deep Learning Tutorials

Neural Network Architectures

A Practical Introduction to Deep Learning with Caffe and Python

Notes on Convolutional Neural Networks

Feed Forward and Backward Run in Deep Convolution Neural Network

Convolutional Networks

Exploring convolutional neural networks with DL4J

Understanding Convolutional Neural Networks

Laws, Sausages and ConvNets

Convolutional Neural Networks (CNNs): An Illustrated Explanation

intro_deep: Introduction tutorials to deep learning with Theano and OpenDeep

Deep Learning on Java by Breandan Considine

Using Convolutional Neural Networks and TensorFlow for Image Classification (NYC TensorFlow meetup)

Neural networks with Theano and Lasagne

Introduction to Deep Learning

Introduction to Deep Learning for Image Recognition - SciPy US 2016

Deep learning tutorials (2nd ed.)

A Beginner’s Guide To Understanding Convolutional Neural Networks

A Beginner’s Guide To Understanding Convolutional Neural Networks Part 2

The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3)

Deep Learning Part 1: Comparison of Symbolic Deep Learning Frameworks

Deep Learning Part 2: Transfer Learning and Fine-tuning Deep Convolutional Neural Networks

Deep Learning Part 3: Combining Deep Convolutional Neural Network with Recurrent Neural Network

Introduction to Deep Learning for Image Processing

The best explanation of Convolutional Neural Networks on the Internet!

The Evolution and Core Concepts of Deep Learning & Neural Networks

An Intuitive Explanation of Convolutional Neural Networks

How Convolutional Neural Networks Work

Preliminary Note on the Complexity of a Neural Network

Deep Learning Tutorial

Jupyter notebooks and code for Intro to DL talk at Genesys

Learn Deep Learning the Hard Way

A Complete Guide on Getting Started with Deep Learning in Python

Deep learning for complete beginners: Recognising handwritten digits

Deep learning for complete beginners: Using convolutional nets to recognise images

Deep learning for complete beginners: neural network fine-tuning techniques

How do Convolutional Neural Networks work?

Creating a Neural Network That Can Tell if a Name Is Male or Female, in JavaScript

Softmax Classifiers Explained

The Softmax function and its derivative

How an algorithm behind Deep Learning works

The Neural Network Zoo

Recognising Beer with TensorFlow

Deep learning architecture diagrams

Getting Started with Deep Learning and Python

Deep Learning Practicals

A simple workflow for deep learning

A primer on universal function approximation with deep learning (in Torch and R)

An Introduction to Implementing Neural Networks using TensorFlow

A Gentle Introduction to Convolutional Neural Networks

Beginning Machine Learning with Keras and TensorFlow

Shortest Way to Deep Learning

Deep learning with Matlab

Convolutional neural networks for computer vision with Matlab

Neural Net Computing Explodes

Tutorial: Optimizing Neural Networks using Keras (with Image recognition case study)

15 Deep Learning Tutorials

Deep Learning Episode 1: Optimizing DeepMind’s A3C on Torch

Deep Learning Episode 2: Scaling TensorFlow over multiple EC2 GPU nodes

Deep Learning Episode 3: Supercomputer vs Pong

Deep Learning Episode 4: Supercomputer vs Pong II

Nuts and Bolts of Applying Deep Learning — Summary

Intro to Deep Learning for Computer Vision

If I Can Learn to Play Atari, I Can Learn TensorFlow

TensorFlow workshop materials

Some theorems on deep learning

Pokemon, Colors, and Deep Learning

Why Deep Learning is Radically Different from Machine Learning

Deep Learning: The Unreasonable Effectiveness of Randomness

Deep Meta-Learning : Machines now Bootstrap Themselves

Are Deep Neural Networks Creative?

Are Deep Neural Networks Creative? v2

Develop/Train A Convolutional Neural Netwok For MNIST Dataset

Rethinking Generalization in Deep Learning

The hard thing about deep learning

The hard thing about deep learning

Introduction to Autoencoders

Two Days to a Demo

Deep Learning Tutorials for 10 Weeks

Deep Learning in Clojure With Cortex

A Guide to Deep Learning by YerevaNN

Learning to Learn, to Program, to Explore and to Seek Knowledge

Have Fun with Machine Learning: A Guide for Beginners

Deep Learning Cheat Sheet

How to train your Deep Neural Network

A deep learning traffic light detector using dlib and a few images from Google street view

Recognizing Traffic Lights With Deep Learning

Tutorials for deep learning

The Holographic Principle: Why Deep Learning Works

Deep Neural Networks - A Brief History

Fundamental Deep Learning code in TFLearn, Keras, Theano and TensorFlow

Deep Neural Network from scratch

Convolutional Neural Networks

Exploring Optimizers

A Gentle Introduction to Exploding Gradients in Neural Networks


Understanding Convolutions

Note on the implementation of a convolutional neural networks

Convolution in Caffe: a memo


An Analysis of Convolution for Inference

Understanding Convolution in Deep Learning

A guide to convolution arithmetic for deep learning

Going beyond full utilization: The inside scoop on Nervana’s Winograd kernels

Playing with convolutions in TensorFlow: From a short introduction to convolution to a complete model

How convolutional neural networks see the world: An exploration of convnet filters with Keras

One by One [ 1 x 1 ] Convolution - counter-intuitively useful

Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize

Receptive Field

A guide to receptive field arithmetic for Convolutional Neural Networks


Why Momentum Really Works


maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

GEMM (General Matrix Matrix Multiply)

Why GEMM is at the heart of deep learning

A full walk through of the SGEMM implementation


Learning representations by back-propagating errors

Learning Internal Representations by Error Propagating

Calculus on Computational Graphs: Backpropagation

Styles of Truncated Backpropagation

Is BackPropagation Necessary?

Backpropagation In Convolutional LSTMs

Backward Pass on Conv Layer

Convolutional Neural Networks backpropagation: from intuition to derivation

Backpropagation In Convolutional Neural Networks

Why do we rotate weights when computing the gradients in a convolution layer of a convolution network?

Note on the implementation of a convolutional neural networks


Attention in a Convolutional Neural Net

Attention-based Networks

Attention in Neural Networks and How to Use It


Hierarchical softmax and negative sampling: short notes worth telling


DIY Deep Learning for Vision: a Hands-On Tutorial with Caffe

Deep learning tutorial on Caffe technology : basic commands, Python and C++ code

Using Caffe with your own dataset

OpenCV 3.0.0-dev: Load Caffe framework models


Chainer Info


Keras tutorial

Keras Tutorial: The Ultimate Beginner’s Guide to Deep Learning in Python

Deep Learning with Keras: Tutorial @ EuroScipy 2016

Transfer Learning and Fine Tuning for Cross Domain Image Classification with Keras


10 Deep Learning projects based on Apache MXNet

Awesome MXNet(Beta)


Optimize Deep Learning GPU Operators with TVM: A Depthwise Convolution Example


Theano Tutorial @ LTI, Carnegie Mellon University

An Introduction to MXNet/Gluon

TensorFlow A beginners guide to a powerful framework.

TensorFlow Examples: TensorFlow tutorials and code examples for beginners

Awesome TensorFlow: A curated list of awesome TensorFlow experiments, libraries, and projects

The Good, Bad, & Ugly of TensorFlow: A survey of six months rapid evolution (+ tips/hacks and code to fix the ugly stuff)

Tensorflow Tutorials using Jupyter Notebook

TensorFlow Tutorial


Introduction to TensorFlow

TensorFlow-Tutorials: Simple tutorials using Google’s TensorFlow Framework

Neural Network Toolbox on TensorFlow

Awesome Tensorflow Implementations

The Ultimate List of TensorFlow Resources: Books, Tutorials & More

Install TensorFlow: Slides and code from our TensorFlow Workshop

A Tour of TensorFlow

TensorFlow Tutorials

Shapes and dynamic dimensions in TensorFlow

TensorFlow saving/restoring and mixing multiple models

Getting to Know TensorFlow

Image Classification and Segmentation with Tensorflow and TF-Slim

Not another MNIST tutorial with TensorFlow

Dive Into TensorFlow

TensorFlow Exercises - focusing on the comparison with NumPy.

A Gentle Guide to Using Batch Normalization in Tensorflow

Using TensorFlow in Windows with a GPU

Tensorflow and deep learning - without a PhD

4 Steps To Learn TensorFlow When You Already Know scikit-learn

Gentlest Introduction to Tensorflow

learn code with tensorflow

TensorFlow Machine Learning Cookbook

TensorFlow Image Recognition on a Raspberry Pi

TensorFlow For Machine Intelligence

Installing TensorFlow on Raspberry Pi 3 (and probably 2 as well)

CodinGame: Deep Learning - TensorFlow

A Practical Guide for Debugging Tensorflow Codes

Debugging Tips on TensorFlow

Tensorflow Projects: Deep learning using tensorflow

Machine Learning with TensorFlow

Convolutional Networks: from TensorFlow to iOS BNNS

Android TensorFlow Machine Learning Example

TensorFlow and Deep Learning Tutorials

Finetuning AlexNet with TensorFlow

Deep Learning examples using Tensorflow

How To Write Your Own Tensorflow in C++

Tensorflow on Android

A Guide to Running Tensorflow Models on Android

TensorFlow Android stand-alone demo


Torch Developer Guide


Practical PyTorch tutorials

The Incredible PyTorch

PyTorch quick start: Classifying an image

tutorial for researchers to learn deep learning with pytorch.

Building a System for Fun!

Facial Recognition On A Jetson TX1 In Tensorflow

Build an AI Cat Chaser with Jetson TX1 and Caffe

Deep Learning in Aerial Systems Using Jetson

Cherry Autonomous Racecar (CAR): NCAT ECE Senior Design Project

Traffic Signs Classification

Traffic signs classification with Deep Learning.

Traffic Sign Recognition with TensorFlow

Traffic signs classification with a convolutional network

Convolutional Neural Network for Traffic Sign Classification — CarND


A Tour of Deep Learning With C++

Published: 09 Oct 2015

Deep Learning Tricks


Practical recommendations for gradient-based training of deep architectures


Efficient BackProp

Deep Learning for Vision: Tricks of the Trade

Optimizing RNN performance

  • intro: Silicon Valley AI Lab
  • keywords: Optimize GEMM, parallel GPU, GRU and LSTM…
  • blog:

Must Know Tips/Tricks in Deep Neural Networks

Training Tricks from Deeplearning4j

Suggestions for DL from Llya Sutskeve

Efficient Training Strategies for Deep Neural Network Language Models

Neural Networks Best Practice

Dark Knowledge from Hinton

Stochastic Gradient Descent Tricks(Leon Bottou)

Advice for applying Machine Learning

How to Debug Learning Algorithm for Regression Model

Large-scale L-BFGS using MapReduce

Selecting good features

– Part I: univariate selection: – Part II: linear models and regularization: – Part III: random forests: – Part IV: stability selection, RFE and everything side by side:


Stochastic Gradient Boosting: Choosing the Best Number of Iterations

Large-Scale High-Precision Topic Modeling on Twitter

H2O World - Top 10 Deep Learning Tips & Tricks - Arno Candel

How To Improve Deep Learning Performance: 20 Tips, Tricks and Techniques That You Can Use To Fight Overfitting and Get Better Generalization

Neural Network Training Speed Trick

The Black Magic of Deep Learning - Tips and Tricks for the practitioner

Published: 09 Oct 2015

Deep Learning Software and Hardware


Accelerating Deep Convolutional Neural Networks Using Specialized Hardware

Installation / Deploying

Setting up a Deep Learning Machine from Scratch (Software): Instructions for setting up the software on your deep learning machine

  • intro: A detailed guide to setting up your machine for deep learning research. Includes instructions to install drivers, tools and various deep learning frameworks. This was tested on a 64 bit machine with Nvidia Titan X, running Ubuntu 14.04
  • github:

How to install CUDA Toolkit and cuDNN for deep learning

Deploying Deep Learning: Guide to deploying deep-learning inference networks and realtime object detection with TensorRT and Jetson TX1.

Install Log

Lessons Learned from Deploying Deep Learning at Scale


All-in-one Docker image for Deep Learning

NVIDIA Docker: GPU Server Application Deployment Made Easy

Deep learning base image for Docker (Tensorflow, Caffe, MXNet, Torch, Openface, etc.)

Deepo: a Docker image with a full reproducible deep learning research environment


SuperVessel Cloud for POWER/OpenPOWER LoginRegisterTutorials

Building Deep Neural Networks in the Cloud with Azure GPU VMs, MXNet and Microsoft R Server

Microsoft open sources its next-gen cloud hardware design

Google Taps AMD For Accelerating Machine Learning In The Cloud

Amazon EC2

Deep Learning AMI on AWS Marketplace

We Have To Go Deeper: AWS p2.xlarge GPU optimized deep learning cluster-grenade

A GPU enabled AMI for Deep Learning

Keras with GPU on Amazon EC2 – a step-by-step instruction

Microsoft R Server

Training Deep Neural Networks on ImageNet Using Microsoft R Server and Azure GPU VMs

Hardware System

I: Building a Deep Learning (Dream) Machine

II: Running a Deep Learning (Dream) Machine

A Full Hardware Guide to Deep Learning

Build your own Deep Learning Box

32-TFLOP Deep Learning GPU Box: A super-fast linux-based machine with multiple GPUs for training deep neural nets

Hands-on with the NVIDIA DIGITS DevBox for Deep Learning

Considerations when setting up deep learning hardware

Building a Workstation for Deep Learning

Deep Learning Machine: First build experience

Building a machine learning/deep learning workstation for under $5000

Hardware Guide: Neural Networks on GPUs (Updated 2016-1-30)

Building Your Own Deep Learning Box

Setting up a Deep learning machine in a lazy yet quick way

Deep Confusion: Misadventures In Building A Deep Learning Machine



Which GPU(s) to Get for Deep Learning: My Experience and Advice for Using GPUs in Deep Learning


GPU折腾手记——2015 (by 李沐)

HPC, Deep Learning and GPUs(2016 Stanford HPC Conference)

Modern GPU 2.0: Design patterns for GPU computing

CuMF: CUDA-Acclerated ALS on mulitple GPUs.

Basic Performance Analysis of NVIDIA GPU Accelerator Cards for Deep Learning Applications

CuPy : NumPy-like API accelerated with CUDA

NumPy GPU acceleration

Efficient Convolutional Neural Network Inference on Mobile GPUs (Embedded Vision Summit)

Deep Learning with Multiple GPUs on Rescale: Torch

GPU-accelerated Theano & Keras on Windows 10 native

NVIDIA Announces Quadro GP100 - Big Pascal Comes to Workstations


Recurrent Neural Networks Hardware Implementation on FPGA

Is implementing deep learning on FPGAs a natural next step after the success with GPUs?

Efficient Implementation of Neural Network Systems Built on FPGAs, Programmed with OpenCL

Deep Learning on FPGAs: Past, Present, and Future

FPGAs Challenge GPUs as a Platform for Deep Learning

Convolution Neural Network CNN Implementation on Altera FPGA using OpenCL

Accelerating Deep Learning Using Altera FPGAs (Embedded Vision Summit)

Machine Learning on FPGAs: Neural Networks

Comprehensive Evaluation of OpenCL-based Convolutional Neural Network Accelerators in Xilinx and Altera FPGAs

Microsoft Goes All in for FPGAs to Build Out AI Cloud

Caffeinated FPGAs: FPGA Framework For Convolutional Neural Networks

Intel Unveils FPGA to Accelerate Neural Networks

Deep Learning with FPGA

A General Neural Network Hardware Architecture on FPGA

Approximate FPGA-based LSTMs under Computation Time Constraints

ARM / Processor

‘Neural network’ spotted deep inside Samsung’s Galaxy S7 silicon brain: Secrets of Exynos M1 cores spilled

Intel will add deep-learning instructions to its processors


ShiDianNao: Shifting Vision Processing Closer to the Sensor


Emerging “Universal” FPGA, GPU Platform for Deep Learning

An Early Look at Startup Graphcore’s Deep Learning Chip

Hardware for Deep Learning


Energy-efficient Hardware for Embedded Vision and Deep Convolutional Neural Networks

Published: 09 Oct 2015

Deep Learning Resources


Published: 09 Oct 2015

Deep Learning Frameworks


Amazon DSSTNE: Deep Scalable Sparse Tensor Network Engine

Apache SINGA


Blocks: A Theano framework for building and training neural networks

Blocks and Fuel: Frameworks for deep learning


BrainCore: The iOS and OS X neural network framework


Brainstorm: Fast, flexible and fun neural networks


Caffe: Convolutional Architecture for Fast Feature Embedding

OpenCL Caffe

Caffe on both Linux and Windows

ApolloCaffe: a fork of Caffe that supports dynamic networks

fb-caffe-exts: Some handy utility libraries and tools for the Caffe deep learning framework

Caffe-Android-Lib: Porting caffe to android platform

caffe-android-demo: An android caffe demo app exploiting caffe pre-trained ImageNet model for image classification

Caffe.js: Run Caffe models in the browser using ConvNetJS

Intel Caffe

  • intro: This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
  • github



Caffe on Mobile Devices


  • intro: Using ARM Compute Library (NEON+GPU) to speed up caffe; Providing utilities to debug, profile and tune application performance
  • github:

Multi-GPU / MPI Caffe

Caffe with OpenMPI-based Multi-GPU support

mpi-caffe: Model-distributed Deep Learning with Caffe and MPI

Caffe-MPI for Deep Learning

Caffe Utils



Caffe2: A New Lightweight, Modular, and Scalable Deep Learning Framework


CDNN2 - CEVA Deep Neural Network Software Framework


Chainer: a neural network framework

Introduction to Chainer: Neural Networks in Python


CNTK: Computational Network Toolkit

An Introduction to Computational Networks and the Computational Network Toolkit


ConvNetJS: Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser


DeepBeliefSDK: The SDK for Jetpac’s iOS, Android, Linux, and OS X Deep Belief image recognition framework


DeepDetect: Open Source API & Deep Learning Server

Deeplearning4j (DL4J)

Deeplearning4j: Deep Learning for Java

Deeplearning4j images for cuda and hadoop.

Deeplearning4J Examples


DeepLearningKit: Open Source Deep Learning Framework for Apple’s tvOS, iOS and OS X

Tutorial — Using DeepLearningKit with iOS for iPhone and iPad


DeepSpark: Deeplearning framework running on Spark


DIGITS: the Deep Learning GPU Training System


dp: A deep learning library for streamlining research and development using the Torch7 distribution


Dragon: A Computation Graph Virtual Machine Based Deep Learning Framework


**DyNet: The Dynamic Neural Network Toolkit **

DyNet Benchmarks


IDLF: The Intel® Deep Learning Framework


Keras: Deep Learning library for Theano and TensorFlow

MarcBS/keras fork

Hera: Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.

Installing Keras for deep learning

Keras Applications - deep learning models that are made available alongside pre-trained weights

Keras resources: Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library

Keras.js: Run trained Keras models in the browser, with GPU support


keras-cn: Chinese keras documents with more examples, explanations and tips.

Kerasify: Small library for running Keras models from a C++ application


Knet: Koç University deep learning framework


Lasagne: Lightweight library to build and train neural networks in Theano


Leaf: The Hacker’s Machine Learning Engine


LightNet: A Versatile, Standalone and Matlab-based Environment for Deep Learning


MatConvNet: CNNs for MATLAB


Marvin: A minimalist GPU-only N-dimensional ConvNet framework

MatConvNet: CNNs for MATLAB


Mocha.jl: Deep Learning for Julia



MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

MXNet Model Gallery: Pre-trained Models of DMLC Project

a short introduction to mxnet design and implementation (chinese)

Deep learning for hackers with MXnet (1) GPU installation and MNIST

mxnet_Efficient, Flexible Deep Learning Framework

Use Caffe operator in MXNet

Deep Learning in a Single File for Smart Devices

MXNet Pascal Titan X benchmark


用MXnet实战深度学习之二:Neural art

Programming Models and Systems Design for Deep Learning

Awesome MXNet

Getting Started with MXNet

gtc_tutorial: MXNet Tutorial for NVidia GTC 2016

MXNET Dependency Engine


WhatsThis-iOS: MXNet WhatThis Example for iOS

MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning



Run trained deep neural networks in the browser or node.js


Neon: Nervana’s Python-based deep learning library

Tools to convert Caffe models to neon’s serialization format

Nervana’s Deep Learning Course


NNabla - Neural Network Libraries by Sony

  • intro: NNabla - Neural Network Libraries NNabla is a deep learning framework that is intended to be used for research, development and production. We aim it running everywhere like desktop PCs, HPC clusters, embedded devices and production servers.
  • homepage:
  • github:


OpenDeep: a fully modular & extensible deep learning framework in Python


OpenNN - Open Neural Networks Library


PaddlePaddle: PArallel Distributed Deep LEarning



Petuum: a distributed machine learning framework


PlaidML: A framework for making deep learning work everywhere


Platoon: Multi-GPU mini-framework for Theano


Poseidon: Distributed Deep Learning Framework on Petuum


Purine: A bi-graph based deep learning framework



Datasets, Transforms and Models specific to Computer Vision

Convert torch to pytorch




TensorDebugger (TDB)

TensorDebugger(TDB): Interactive, node-by-node debugging and visualization for TensorFlow

ofxMSATensorFlow: OpenFrameworks addon for Google’s data-flow graph based numerical computation / machine intelligence library TensorFlow.

TFLearn: Deep learning library featuring a higher-level API for TensorFlow

TensorFlow on Spark


TensorFlow.jl: A Julia wrapper for the TensorFlow Python library

TensorLayer: Deep learning and Reinforcement learning library for TensorFlow

OpenCL support for TensorFlow

Pretty Tensor: Fluent Networks in TensorFlow

Rust language bindings for TensorFlow

TensorFlow Ecosystem: Integration of TensorFlow with other open-source frameworks

Caffe to TensorFlow

TensorFlow Mobile


TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

TensorFlow: A system for large-scale machine learning

TensorFlow Distributions


TensorFlow 官方文档中文版



Theano-Tutorials: Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano

Theano: A Python framework for fast computation of mathematical expressions

Configuring Theano For High Performance Deep Learning

Theano: a short practical guide

Ian Goodfellow’s Tutorials on Theano

Plato: A library built on top of Theano

Theano Windows Install Guide

Theano-MPI: a Theano-based Distributed Training Framework

tiny-dnn (tiny-cnn)

tiny-dnn: A header only, dependency-free deep learning framework in C++11

Deep learning with C++ - an introduction to tiny-dnn



loadcaffe: Load Caffe networks in Torch7

Applied Deep Learning for Computer Vision with Torch

pytorch: Python wrappers for torch and lua

Torch Toolbox: A collection of snippets and libraries for Torch

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

Torchnet: An Open-Source Platform for (Deep) Learning Research

THFFmpeg: Torch bindings for FFmpeg (reading videos only)

caffegraph: Load Caffe networks in Torch7 using nngraph

Optimized-Torch: Intel Torch is dedicated to improving Torch performance when running on CPU

Torch Video Tutorials

Torch in Action


VELES: Distributed platform for rapid Deep learning application development


WebDNN: Fastest DNN Execution Framework on Web Browser


Yann: Yet Another Neural Network Toolbox


Easy benchmarking of all publicly accessible implementations of convnets

Stanford DAWN Deep Learning Benchmark (DAWNBench) - An End-to-End Deep Learning Benchmark and Competition


Deep Learning Implementations and Frameworks (DLIF)


Comparative Study of Deep Learning Software Frameworks

Benchmarking State-of-the-Art Deep Learning Software Tools


TensorFuse: Common interface for Theano, CGT, and TensorFlow

DeepRosetta: An universal deep learning models conversor

Deep Learning Model Convertors


Frameworks and Libraries for Deep Learning

TensorFlow vs. Theano vs. Torch

Evaluation of Deep Learning Toolkits

Deep Machine Learning libraries and frameworks

Torch vs Theano

Deep Learning Software: NVIDIA Deep Learning SDK

A comparison of deep learning frameworks

TensorFlow Meets Microsoft’s CNTK

Is there a case for still using Torch, Theano, Brainstorm, MXNET and not switching to TensorFlow?

  • reddit: [][]

DL4J vs. Torch vs. Theano vs. Caffe vs. TensorFlow

Popular Deep Learning Libraries

The simple example of Theano and Lasagne super power

Comparison of deep learning software

A Look at Popular Machine Learning Frameworks

5 Deep Learning Projects You Can No Longer Overlook

Comparison of Deep Learning Libraries After Years of Use

Deep Learning Part 1: Comparison of Symbolic Deep Learning Frameworks

Deep Learning Frameworks Compared

DL4J vs. Torch vs. Theano vs. Caffe vs. TensorFlow

Deep Learning frameworks: a review before finishing 2016

The Anatomy of Deep Learning Frameworks

Python Deep Learning Frameworks Reviewed

Apple’s deep learning frameworks: BNNS vs. Metal CNN

Published: 09 Oct 2015

Deep learning Courses

Deep Learning

EECS 598: Unsupervised Feature Learning

NVIDIA’s Deep Learning Courses

ECE 6504 Deep Learning for Perception

University of Oxford: Machine Learning: 2014-2015

University of Birmingham 2014: Introduction to Neural Computation (Level 4/M); Neural Computation (Level 3/H)(by John A. Bullinaria)

CMU: Deep Learning

stat212b: Topics Course on Deep Learning for Spring 2016

Good materials on deep learning

Deep Learning: Course by Yann LeCun at Collège de France 2016(Slides in English)

CSC321 Winter 2015: Introduction to Neural Networks

ELEG 5040: Advanced Topics in Signal Processing (Introduction to Deep Learning)

Self-Study Courses for Deep Learning (NVIDIA Deep Learning Institute)

Introduction to Deep Learning

Deep Learning Courses

Creative Applications of Deep Learning w/ Tensorflow

Deep Learning School: September 24-25, 2016 Stanford, CA

CSC 2541 Fall 2016: Differentiable Inference and Generative Models

CS 294-131: Special Topics in Deep Learning (Fall, 2016)

Fork of Lempitsky DL for HSE master students.

ELEG 5040: Advanced Topics in Signal Processing (Introduction to Deep Learning)

CS 20SI: Tensorflow for Deep Learning Research

Deep Learning with TensorFlow

Deep Learning course

CSE 599G1: Deep Learning System

CSC 321 Winter 2017: Intro to Neural Networks and Machine Learning

Theories of Deep Learning (STATS 385)

With Video Lectures

Deep Learning: Taking machine learning to the next level (Udacity)

Neural networks class - Université de Sherbrooke

Deep Learning: Theoretical Motivations

University of Waterloo: STAT 946 - Deep Learning

Deep Learning (2016) - BME 595A, Eugenio Culurciello, Purdue University


Practical Deep Learning For Coders, Part 1

T81-558:Applications of Deep Neural Networks

CS294-129 Designing, Visualizing and Understanding Deep Neural Networks

MIT 6.S191: Introduction to Deep Learning

Edx: Deep Learning Explained

Computer Vision

Stanford CS231n: Convolutional Neural Networks for Visual Recognition (Spring 2017)

Stanford CS231n: Convolutional Neural Networks for Visual Recognition (Winter 2016)

ITP-NYU - Spring 2016

Deep Learning for Computer Vision Barcelona: Summer seminar UPC TelecomBCN (July 4-8, 2016)

DLCV - Deep Learning for Computer Vision

Natural Language Processing

CS224n: Natural Language Processing with Deep Learning

Course notes for CS224N Winter17

Stanford CS224d: Deep Learning for Natural Language Processing

Code for Stanford CS224D: deep learning for natural language understanding

CMU CS 11-747, Fall 2017: Neural Networks for NLP

Deep Learning for NLP - Lecture October 2015

Harvard University: CS287: Natural Language Processing

Deep Learning for Natural Language Processing: 2016-2017

GPU Programming

Course on CUDA Programming on NVIDIA GPUs, July 27–31, 2015

An Introduction to GPU Programming using Theano

GPU Programming

Parallel Programming

Intro to Parallel Programming Using CUDA to Harness the Power of GPUs (Udacity)–cs344


Deep Learning: Theory, Algorithms, and Applications


Open Source Deep Learning Curriculum

Published: 09 Oct 2015

Deep Learning Applications


Published: 09 Oct 2015