Learning Tensorflow: A Guide to Building Deep Learning Systems

Contents
Preface
Introduction
	Going Deep
	TensorFlow: What’s in a Name?
	A High-Level Overview
	Summary
Up & Running with TensorFlow
	Installing TensorFlow
	Hello World
	MNIST
	Softmax Regression
	Summary
TensorFlow Basics
	Computation Graphs
	Graphs, Sessions, and Fetches
	Flowing Tensors
	Variables, Placeholders, and Simple Optimization
	Summary
Convolutional Neural Networks
	Introduction to CNNs
	MNIST: Take II
	CIFAR10
	Summary
Text & Sequences & Visualization
	The Importance of Sequence Data
	Introduction to Recurrent Neural Networks
	RNN for Text Sequences
	Summary
Word Vectors, Advanced RNN & embedding Visualization
	Introduction to Word Embeddings
	Word2vec
	Pretrained Embeddings, Advanced RNN
	Summary
TensorFlow Abstractions & Simplification
	Chapter Overview
	contrib.learn
	TFLearn
	Summary
Queues Threads & Reading Data
	The Input Pipeline
	TFRecords
	Queues
	A Full Multithreaded Input Pipeline
	Summary
Distributed TensorFlow
	Distributed Computing
	TensorFlow Elements
	Distributed Example
	Summary
Exporting & Serving Models
	Saving and Exporting Our Model
	Introduction to TensorFlow Serving
	Summary
Model Construction & TensorFlow Serving
	Model Structuring and Customization
	Required and Recommended Components for TensorFlow Serving
Index