This is the official code repository for Machine Learning with TensorFlow.
Get started with machine learning using TensorFlow, Google's latest and greatest machine learning library.
Summary
Chapter 2  TensorFlow Basics

Concept 1: Defining tensors

Concept 2: Evaluating ops

Concept 3: Interactive session

Concept 4: Session loggings

Concept 5: Variables

Concept 6: Saving variables

Concept 7: Loading variables

Concept 8: TensorBoard

Concept 1: Linear regression

Concept 2: Polynomial regression

Concept 3: Regularization

Concept 1: Linear regression for classification

Concept 2: Logistic regression

Concept 3: 2D Logistic regression

Concept 4: Softmax classification

Concept 1: Clustering

Concept 2: Segmentation

Concept 3: Selforganizing map
Chapter 6  Hidden markov models

Concept 1: Forward algorithm

Concept 2: Viterbi decode

Concept 1: Autoencoder

Concept 2: Applying an autoencoder to images

Concept 3: Denoising autoencoder
Chapter 8  Reinforcement learning

Concept 1: Reinforcement learning
Chapter 9  Convolutional Neural Networks

Concept 1: Using CIFAR10 dataset

Concept 2: Convolutions

Concept 3: Convolutional neural network
Chapter 10  Recurrent Neural Network

Concept 1: Loading timeseries data

Concept 2: Recurrent neural networks

Concept 3: Applying RNN to realworld data for timeseries prediction

Concept 1: Multicell RNN

Concept 2: Embedding lookup

Concept 3: Seq2seq model

Concept 1: RankNet

Concept 2: Image embedding

Concept 3: Image ranking