The Ultimate List of TensorFlow Resources: Books, Tutorials in 2019

The Ultimate List of TensorFlow Resources: Books, Tutorials

TensorFlow is an open source software library for numerical computation utilizing data flow graphs. The graph nodes speak to mathematical operations, while the graph edges speak to the multidimensional data arrays (tensors) that flow between them. This adaptable architecture gives you a chance to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes TensorBoard, a data visualization toolkit.

TensorFlow was initially created by researchers and engineers working on the Google Brain team inside Google’s Machine Intelligence Research organization for the reasons of conducting machine learning and deep neural networks research. The system is sufficiently general to be applicable in a wide assortment of other domains, as well.

You must Watch this below 2 hours video TensorFlow and Deep Learning – without a PhD.

Below are some of the Ultimate Collection List of Tensor Flow resources gathered with a good portion of tutorials and online courses that can help you to Self-study TensorFlow framework on your own! Please feel free to suggest more materials in the comments!

BOOKS

Getting Started with TensorFlow by Giancarlo Zaccone
First Contact with TensorFlow by Jordi Torres, professor at UPC Barcelona Tech and a research manager and senior advisor at Barcelona Supercomputing Center
Deep Learning with Python – Develop Deep Learning Models on Theano and TensorFlow Using Keras by Jason Brownlee

VIDEOS

TensorFlow Guide 1 – A guide to installation and use
TensorFlow Guide 2 – Continuation of first video
TensorFlow Basic Usage – A guide going over basic usage
Some useful TensorFlow related videos on YouTube – Must Watch
TensorFlow Deep MNIST for Experts – Goes over Deep MNIST
TensorFlow Udacity Deep Learning – Basic steps to install TensorFlow for free on the Cloud 9 online service with 1Gb of data
Why Google wants everyone to have access to TensorFlow
Videos from TensorFlow Silicon Valley Meet Up 1/19/2016
Videos from TensorFlow Silicon Valley Meet Up 1/21/2016
Stanford CS224d Lecture 7 – Introduction to TensorFlow, 19th Apr 2016 – CS224d Deep Learning for Natural Language Processing by Richard Socher
Diving into Machine Learning through TensorFlow – Pycon 2016 Portland Oregon, Slide& Code by Julia Ferraioli, Amy Unruh, Eli Bixby
TensorFlow in 5 Minutes
Large Scale Deep Learning with TensorFlow – Spark Summit 2016 Keynote by Jeff Dean

LIBRARIES

Scikit Flow (TF Learn) – Simplified interface for Deep/Machine Learning (now part of TensorFlow)
tflearn – Deep learning library featuring a higher-level API
ensorFrames – TensorFlow binding for Apache Spark
caffe-tensorflow – Convert Caffe models to TensorFlow format
keras – Minimal, modular deep learning library for TensorFlow and Theano
A TensorFlow implementation of the models described in Globally Normalized Transition-Based Neural Networks, Andor et al. (2016)

TUTORIALS

TensorFlow Tutorial 1 – From the basics to slightly more interesting applications of TensorFlow
TensorFlow Tutorial 2 – Introduction to deep learning based on Google’s TensorFlow framework. These tutorials are direct ports of Newmu’s Theano
TensorFlow Examples – TensorFlow tutorials and code examples for beginners
Sungjoon’s TensorFlow-101 – TensorFlow tutorials written in Python with Jupyter Notebook
Terry Um’s TensorFlow Exercises – Re-create the codes from other TensorFlow examples
Installing TensorFlow on Raspberry Pi 3 – TensorFlow compiled and running properly on the Raspberry Pi

FEW PROJECTS

Pretty Tensor – Pretty Tensor provides a high level builder API
Neural Style – An implementation of neural style
TensorFlow White Paper Notes – Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation
NeuralArt – Implementation of A Neural Algorithm of Artistic Style
Generative Handwriting Demo using TensorFlow – An attempt to implement the random handwriting generation portion of Alex Graves’ paper
Neural Turing Machine in TensorFlow – implementation of Neural Turing Machine
GoogleNet Convolutional Neural Network Groups Movie Scenes By Setting – Search, filter, and describe videos based on objects, places, and other things that appear in them
Neural machine translation between the writings of Shakespeare and modern English using TensorFlow – This performs a monolingual translation, going from modern English to Shakespeare and vis-versa.
Colornet – Neural Network to colorize grayscale images – Neural Network to colorize grayscale images
Neural Caption Generator – Implementation of “Show and Tell”
Neural Caption Generator with Attention – Implementation of “Show, Attend and Tell”
Weakly_detector – Implementation of “Learning Deep Features for Discriminative Localization”
Dynamic Capacity Networks – Implementation of “Dynamic Capacity Networks”
HMM in TensorFlow – Implementation of viterbi and forward/backward algorithms for HMM
DeepOSM – Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.
DQN-tensorflow – Tensorflow implementation of DeepMind’s ‘Human-Level Control through Deep Reinforcement Learning’ with OpenAI Gym by Devsisters.com
Highway Network – Tensorflow implementation of “Training Very Deep Networks” with a blog post
Sentence Classification with CNN – Tensorflow implementation of “Convolutional Neural Networks for Sentence Classification” with a blog post

PAPERS

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems – This paper describes the TensorFlow interface and an implementation of that interface that we have built at Google
Comparative Study of Deep Learning Software Frameworks – The study is performed on several types of deep learning architectures and we evaluate the performance of the above frameworks when employed on a single machine for both (multi-threaded) CPU and GPU (Nvidia Titan X) settings
Distributed TensorFlow with MPI – In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI)
Globally Normalized Transition-Based Neural Networks – This paper describes the models behind SyntaxNet.
TensorFlow: A system for large-scale machine learning – This paper describes the TensorFlow dataflow model in contrast to existing systems and demonstrate the compelling performance

COMMUNITY

BEST ARTICLES ON TENSORFLOW

TensorFlow for Poets – Goes over the implementation of TensorFlow
Introduction to Scikit Flow – Simplified Interface to TensorFlow – Key Features Illustrated
Building Machine Learning Estimator in TensorFlow – Understanding the Internals of TensorFlow Learn Estimators
The indico Machine Learning Team’s take on TensorFlow
The Good, Bad, & Ugly of TensorFlow – A survey of six months rapid evolution (+ tips/hacks and code to fix the ugly stuff), Dan Kuster at Indico, May 9, 2016
Fizz Buzz in TensorFlow – A joke by Joel Grus
TensorFlow: smarter machine learning, for everyone – An introduction to TensorFlow

GITHUB

Magenta – Research project to advance the state of the art in machine intelligence for music and art generation.
YOLO TensorFlow – Implementation of ‘YOLO : Real-Time Object Detection’

OPEN-source neural network framework

Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source – Release of SyntaxNet, “an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding systems.

FURTHER READING