This page lists the links to useful TensorFlow resources from nonofficial TensorFlow webiste.
 Book: Machine Learning with TensorFlow (Github, tensorflowbook)
 Dr. Andy Thomas’s great tutorial: Python TensorFlow Tutorial – Build a Neural Network (pdf). You will get a pretty good sense of how TensorFlow works. If you have played with machine learning and TensorFlow for a while, I recommend reading his tips and tricks post (pdf).
See his another post Convolutional Neural Networks Tutorial in TensorFlow (pdf) for a very good illustration and explanation about how CNN works and it is implementation in TensorFlow.
 Check out this GIF animation on Justin Francis’ twitter for a visual and intuitive training evolution of deep neural networks. If you want to dig into more details about this, check out his tutorial: Not another MNIST tutorial with TensorFlow (pdf). You might be interested in Justin’s another tutorial post: Dive into TensorFlow with Linux (pdf).
 A course offered at Stanford University: Tensorflow for Deep Learning Research (Course syllabus, Github repo)
 Some good posts about TensorFlow from Danijar Hafner about TensorFlow usages.
 TensorFlow for Poets &TensorFlow for Mobile Poets (pretty good basic intro to TensorFlow)
 A very good stepbystep learning guide about TensorFlow.
 A TensorFlow Tutorial: Email Classification (Feb 1, 2016 by Josh Meyer)
It contains sample code for feeding customized training data set from csv files. It used a simple logistic regression classifier to classify Emails.
 ScikitLearn style wrapper for TensorFlow: skflow – Simplified Interface for TensorFlow for Deep Learning.
 Udacity Deep Learning MOOC assignments by ArnO on Github
 TensorFlow tutorials on Github by nlintz.
Simple tutorials using Google’s TensorFlow Framework. Dependencies: TensorFlow ; Numpy; matplotlib.
 More tensorflow tutorials on Github by pkmital
From the basics to slightly more interesting applications of Tensorflow.
 Another TensorFlow Examples on Github by aymericdamien.
 TensorFlow Workshop on Github

 Recurrent Neural Networks (RNN) – Deep Learning with Neural Networks and TensorFlow (Published on Sep 13, 2016 by sentdex)
In this Deep Learning with TensorFlow tutorial, it covers the basics of the Recurrent Neural Network, along with the LSTM (Long Short Term Memory) cell, which is a very common RNN cell used.
 VGG in TensorFlow (Jun 17, 2016)

Using a GPU (from learningtensorflow.com)
 Matrix Factorization with Tensorflow (Mar 11, 2016)
*****Distributed TensorFlow*****
 Distributed TensorFlow on Spark (on Github, slideshare, Blog post, presentation video)
 Large Scale Deep Learning with TensorFlow (Using Spark, YouTube Video)
 TensorFrames: Google Tensorflow on Apache Spark

Distributed TensorFlow examples (from learningtensorflow.com)
includes examples of a single process, and multiple processes.
 Distributed Tensorflow Example (by Imanol Schlag)
 Recurrent Neural Networks (RNN) – Deep Learning with Neural Networks and TensorFlow (Published on Sep 13, 2016 by sentdex)
A brief tutorial on how to do asynchronous and data parallel training using three worker machines with each one using a GTX 960 GPU (2GB) and one parameter server with no GPU. I use a simple sigmoid network with a small learning rate to measure performance differences on MNIST. The goal is not to achieve a high accuracy but to learn about tensorflows distribution capabilities.