Acceleration and Model Compression


Published: 09 Oct 2015

Graph Convolutional Networks

Learning Convolutional Neural Networks for Graphs

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

Semi-Supervised Classification with Graph Convolutional Networks

Graph Based Convolutional Neural Network

How powerful are Graph Convolutions? (review of Kipf & Welling, 2016)

Graph Convolutional Networks

DeepGraph: Graph Structure Predicts Network Growth

Deep Learning with Sets and Point Clouds

Deep Learning on Graphs

Robust Spatial Filtering with Graph Convolutional Neural Networks

Modeling Relational Data with Graph Convolutional Networks

Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

Deep Learning on Graphs with Graph Convolutional Networks

Deep Learning on Graphs with Keras

Learning Graph While Training: An Evolving Graph Convolutional Neural Network

Graph Attention Networks

Residual Gated Graph ConvNets

Probabilistic and Regularized Graph Convolutional Networks

Videos as Space-Time Region Graphs

Relational inductive biases, deep learning, and graph networks

Can GCNs Go as Deep as CNNs?

GMNN: Graph Markov Neural Networks

DeepGCNs: Making GCNs Go as Deep as CNNs

Rethinking pooling in graph neural networks

Published: 09 Oct 2015

Generative Adversarial Networks

Generative Adversarial Networks

Generative Adversarial Nets

Adversarial Feature Learning

Generative Adversarial Networks

Adversarial Examples and Adversarial Training

How to Train a GAN? Tips and tricks to make GANs work

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Learning Interpretable Latent Representations with InfoGAN: A tutorial on implementing InfoGAN in Tensorflow

Coupled Generative Adversarial Networks

Energy-based Generative Adversarial Network

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

Connecting Generative Adversarial Networks and Actor-Critic Methods

Generative Adversarial Nets from a Density Ratio Estimation Perspective

Unrolled Generative Adversarial Networks

Generative Adversarial Networks as Variational Training of Energy Based Models

Multi-class Generative Adversarial Networks with the L2 Loss Function

Least Squares Generative Adversarial Networks

Inverting The Generator Of A Generative Adversarial Networ


Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks

Associative Adversarial Networks

Temporal Generative Adversarial Nets

Handwriting Profiling using Generative Adversarial Networks

  • intro: Accepted at The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17 Student Abstract and Poster Program)
  • arxiv:

C-RNN-GAN: Continuous recurrent neural networks with adversarial training

Ensembles of Generative Adversarial Networks

Improved generator objectives for GANs

Stacked Generative Adversarial Networks

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

AdaGAN: Boosting Generative Models

Towards Principled Methods for Training Generative Adversarial Networks

Wasserstein GAN

Improved Training of Wasserstein GANs

On the effect of Batch Normalization and Weight Normalization in Generative Adversarial Networks

On the Effects of Batch and Weight Normalization in Generative Adversarial Networks

Controllable Generative Adversarial Network

Generative Adversarial Networks: An Overview

  • intro: Imperial College London & Victoria University of Wellington & University of Montreal & Cortexica Vision Systems Ltd
  • intro: IEEE Signal Processing Magazine Special Issue on Deep Learning for Visual Understanding
  • arxiv:

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Spectral Normalization for Generative Adversarial Networks

Are GANs Created Equal? A Large-Scale Study

GAGAN: Geometry-Aware Generative Adverserial Networks

CycleGAN: a Master of Steganography

PacGAN: The power of two samples in generative adversarial networks

ComboGAN: Unrestrained Scalability for Image Domain Translation

Decoupled Learning for Conditional Adversarial Networks

No Modes left behind: Capturing the data distribution effectively using GANs

Improving GAN Training via Binarized Representation Entropy (BRE) Regularization

On GANs and GMMs

The Unusual Effectiveness of Averaging in GAN Training

Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis

The GAN Landscape: Losses, Architectures, Regularization, and Normalization

Which Training Methods for GANs do actually Converge?

Convergence Problems with Generative Adversarial Networks (GANs)

Bayesian CycleGAN via Marginalizing Latent Sampling

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

Do GAN Loss Functions Really Matter?

Image-to-Image Translation


Image-to-Image Translation with Conditional Adversarial Networks

Remastering Classic Films in Tensorflow with Pix2Pix

Image-to-Image Translation in Tensorflow

webcam pix2pix

Unsupervised Image-to-Image Translation with Generative Adversarial Networks

Unsupervised Image-to-Image Translation Networks

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

CycleGAN and pix2pix in PyTorch

Perceptual Adversarial Networks for Image-to-Image Transformation

XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings

In2I : Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

Discriminative Region Proposal Adversarial Networks for High-Quality Image-to-Image Translation

Toward Multimodal Image-to-Image Translation

Face Translation between Images and Videos using Identity-aware CycleGAN

Unsupervised Multi-Domain Image Translation with Domain-Specific Encoders/Decoders

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

On the Effectiveness of Least Squares Generative Adversarial Networks

GANs for Limited Labeled Data

Defending Against Adversarial Examples

Conditional Image-to-Image Translation

XOGAN: One-to-Many Unsupervised Image-to-Image Translation

Unsupervised Attention-guided Image to Image Translation

Exemplar Guided Unsupervised Image-to-Image Translation

Improving Shape Deformation in Unsupervised Image-to-Image Translation

Video-to-Video Synthesis

Segmentation Guided Image-to-Image Translation with Adversarial Networks

ForkGAN: Seeing into the rainy night


Generative Adversarial Networks with Keras

Generative Adversarial Network Demo for Fresh Machine Learning #2

TextGAN: A generative adversarial network for text generation, written in TensorFlow.

cleverhans v0.1: an adversarial machine learning library

Deep Convolutional Variational Autoencoder w/ Adversarial Network

A versatile GAN(generative adversarial network) implementation. Focused on scalability and ease-of-use.

AdaGAN: Boosting Generative Models

TensorFlow-GAN (TFGAN)


Generative Adversial Networks Explained

Generative Adversarial Autoencoders in Theano

An introduction to Generative Adversarial Networks (with code in TensorFlow)

Difficulties training a Generative Adversarial Network

Are Energy-Based GANs any more energy-based than normal GANs?

Generative Adversarial Networks Explained with a Classic Spongebob Squarepants Episode: Plus a Tensorflow tutorial for implementing your own GAN

Deep Learning Research Review Week 1: Generative Adversarial Nets

Stability of Generative Adversarial Networks

Instance Noise: A trick for stabilising GAN training

Generating Fine Art in 300 Lines of Code

Talks / Videos

Generative Adversarial Network visualization


The GAN Zoo

AdversarialNetsPapers: The classical Papers about adversial nets

GAN Timeline

Published: 09 Oct 2015

Fun With Deep Learning


Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting


Brewing EmojiNet

Image2Emoji: Zero-shot Emoji Prediction for Visual Media

Teaching Robots to Feel: Emoji & Deep Learning 👾 💭 💕

Text input with relevant emoji sorted with deeplearning


Sketch-a-Net that Beats Humans

How Do Humans Sketch Objects?

Learning to Simplify: Fully Convolutional Networks for Rough Sketch Cleanup (SIGGRAPH 2016)

Convolutional Sketch Inversion

Sketch Me That Shoe (CVPR 2016)

Mastering Sketching: Adversarial Augmentation for Structured Prediction

SketchyGAN: Towards Diverse and Realistic Sketch to Image Synthesis

Image Colorization

Deep Colorization

Learning Large-Scale Automatic Image Colorization

Learning Representations for Automatic Colorization

Colorful Image Colorization

Colorising Black & White Photos using Deep Learning

Automatic Colorization (Tensorflow + VGG)

colornet: Neural Network to colorize grayscale images

Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification (SIGGRAPH 2016)

Convolutional autoencoder to colorize greyscale images

Image-Color: A deep learning approach to colorizing images

Creating an artificial artist: Color your photos using Neural Networks

Paints Chainer: line drawing colorization using chainer

Unsupervised Diverse Colorization via Generative Adversarial Networks

(DE)^2 CO: Deep Depth Colorization

A Neural Representation of Sketch Drawings

Real-Time User-Guided Image Colorization with Learned Deep Priors

PixColor: Pixel Recursive Colorization

cGAN-based Manga Colorization Using a Single Training Image

Interactive Deep Colorization With Simultaneous Global and Local Inputs

Image Colorization with Generative Adversarial Networks

Learning to Color from Language

Deep Exemplar-based Colorization

Pixel-level Semantics Guided Image Colorization

User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks

Pixelated Semantic Colorization

Colorization Transformer


Visually Indicated Sounds


GRUV: Algorithmic Music Generation using Recurrent Neural Networks

DeepHear - Composing and harmonizing music with neural networks

Using AutoHarp and a Character-Based RNN to Create MIDI Drum Loops

Musical Audio Synthesis Using Autoencoding Neural Nets

sound-rnn: Generating sound using recurrent neural networks

Using LSTM Recurrent Neural Networks for Music Generation (Project for AI Prac Fall 2015 at Cornell)

Visually Indicated Sounds (MIT. 2015)

Training a Recurrent Neural Network to Compose Music

LSTM Realbook

LSTMetallica: Generation drum tracks by learning the drum tracks of 60 Metallica songs

deepjazz: Deep learning driven jazz generation using Keras & Theano!

Magenta: Music and Art Generation with Machine Intelligence

Music Transcription with Convolutional Neural Networks

Long Short-Term Memory Recurrent Neural Network Architectures for Generating Music and Japanese Lyrics

BachBot: Use deep learning to generate and harmonize music in the style of Bach

Generate Music in TensorFlow

Generate new lyrics in the style of any artist using LSTMs and TensorFlow

sound-GAN: Generative Adversial Network for music composition

Analyzing Six Deep Learning Tools for Music Generation

WIMP2: Creating Music with AI: Highlights of Current Research

Song From PI: A Musically Plausible Network for Pop Music Generation

Grammar Argumented LSTM Neural Networks with Note-Level Encoding for Music Composition


Hip-Hop - Generating lyrics with RNNs

Metis Final Project: Music Composition with LSTMs

Neural Translation of Musical Style


NeuralSnap: Generates poetry from images using convolutional and recurrent neural networks

Generating Chinese Classical Poems with RNN Encoder-Decoder

Chinese Poetry Generation with Planning based Neural Network

Weiqi (Go)

Teaching Deep Convolutional Neural Networks to Play Go

Move Evaluation in Go Using Deep Convolutional Neural Networks(Google DeepMind, Google Brain)

Training Deep Convolutional Neural Networks to Play Go

Computer Go Research - The Challenges Ahead (Martin Müller. IEEE CIG 2015)

GoCNN: Using CNN for Go (Weiqi/Baduk) board evaluation with tensorflow

DarkGo: Go in Darknet

BetaGo: Go bots for the people

Deep Learning and the Game of Go


Better Computer Go Player with Neural Network and Long-term Prediction (Facebook AI Research)


Mastering the game of Go with deep neural networks and tree search

AlphaGo Teach


How Alphago Works

AlphaGo in Depth


  • intro: Leela is a strong Go playing program combining advances in Go programming and further original research into a small, easy to use graphical interface.
  • homepage:

Mastering the game of Go without human knowledge

Computer Go & AlphaGo Zero

AlphaZero: Mastering Games without Human Knowledge - NIPS 2017


The future is here – AlphaZero learns chess

AlphaGo Zero Cheat Sheet


Giraffe: Using Deep Reinforcement Learning to Play Chess

Spawkfish: neural network based chess engine

Chess position evaluation with convolutional neural network in Julia

Deep Learning for … Chess

DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm


Learning Game of Life with a Convolutional Neural Network

Reinforcement Learning using Tensor Flow: A deep Q learning demonstration using Google Tensorflow

Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games Using Convolutional Networks

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games

BlizzCon 2016 DeepMind and StarCraft II Deep Learning Panel Transcript

DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker

Gym StarCraft: StarCraft environment for OpenAI Gym, based on Facebook’s TorchCraft

  • intro: Gym StarCraft is an environment bundle for OpenAI Gym. It is based on Facebook’s TorchCraft, which is a bridge between Torch and StarCraft for AI research.
  • github:

Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games

Learning Macromanagement in StarCraft from Replays using Deep Learning

Multi-platform Version of StarCraft: Brood War in a Docker Container: Technical Report

Macro action selection with deep reinforcement learning in StarCraft


DeepLeague: leveraging computer vision and deep learning on the League of Legends mini map + giving away a dataset of over 100,000 labeled images to further esports analytics research

DeepLeague (Part 2): The Technical Details


Learning Machines

Learning Bit by Bit


Machine learning for artists @ ITP-NYU, Spring 2016

Machine Learning for Artists @ OpenDot, November 2016

The Neural Aesthetic @ SchoolOfMa, Summer 2016


Review of machine / deep learning in an artistic context

Apprentice Work

Exploring the Intersection of Art and Machine Intelligence

Using machine learning to generate music

art in the age of machine intelligence

Understanding Aesthetics with Deep Learning

Go, Marvin Minsky, and the Chasm that AI Hasn’t Yet Crossed


A Return to Machine Learning


Music, Art and Machine Intelligence Workshop 2016

Published: 09 Oct 2015

Face Recognition


Published: 09 Oct 2015

Deep Learning with Machine Learning


Published: 09 Oct 2015

Deep Learning Tutorials


Deep learning

Toward Theoretical Understanding of 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

Only Numpy: (Why I do Manual Back Propagation) Implementing Multi Channel/Layer Convolution Neural Network on Numpy with Interactive Code

92.45% on CIFAR-10 in Torch


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

Bag of Tricks for Image Classification with Convolutional Neural Networks


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