B05478_Deep Learning With TensorFlow by Publishing, Packt -- Read -- Imperial Library of Trantor

Index

Title Page Copyright Credits About the Authors About the Reviewers www.PacktPub.com Customer Feedback Preface

What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support

Downloading the example code Downloading the color images of this book Errata Piracy Questions

Getting Started with Deep Learning

Introducing machine learning

Supervised learning Unsupervised learning Reinforcement learning

What is deep learning?

How the human brain works Deep learning history Problems addressed

Neural networks

The biological neuron An artificial neuron

How does an artificial neural network learn?

The backpropagation algorithm Weights optimization Stochastic gradient descent

Neural network architectures

Multilayer perceptron DNNs architectures Convolutional Neural Networks Restricted Boltzmann Machines

Autoencoders Recurrent Neural Networks Deep learning framework comparisons Summary

First Look at TensorFlow

General overview

What's new with TensorFlow 1.x? How does it change the way people use it? Installing and getting started with TensorFlow

Installing TensorFlow on Linux

Which TensorFlow to install on your platform?

Requirements for running TensorFlow with GPU from NVIDIA

Step 1: Install NVIDIA CUDA Step 2: Installing NVIDIA cuDNN v5.1+ Step 3: GPU card with CUDA compute capability 3.0+ Step 4: Installing the libcupti-dev library Step 5: Installing Python (or Python3) Step 6: Installing and upgrading PIP (or PIP3) Step 7: Installing TensorFlow

How to install TensorFlow

Installing TensorFlow with native pip Installing with virtualenv

Installing TensorFlow on Windows

Installation from source Install on Windows Test your TensorFlow installation

Computational graphs Why a computational graph?

Neural networks as computational graphs

The programming model Data model

Rank Shape Data types Variables Fetches Feeds

TensorBoard

How does TensorBoard work?

Implementing a single input neuron Source code for the single input neuron Migrating to TensorFlow 1.x

How to upgrade using the script Limitations Upgrading code manually Variables Summary functions Simplified mathematical variants Miscellaneous changes

Summary

Using TensorFlow on a Feed-Forward Neural Network

Introducing feed-forward neural networks

Feed-forward and backpropagation Weights and biases Transfer functions

Classification of handwritten digits Exploring the MNIST dataset Softmax classifier

Visualization

How to save and restore a TensorFlow model

Saving a model Restoring a model Softmax source code Softmax loader source code

Implementing a five-layer neural network

Visualization Five-layer neural network source code

ReLU classifier Visualization

Source code for the ReLU classifier

Dropout optimization Visualization

Source code for dropout optimization

Summary

TensorFlow on a Convolutional Neural Network

Introducing CNNs CNN architecture

A model for CNNs - LeNet

Building your first CNN

Source code for a handwritten classifier

Emotion recognition with CNNs

Source code for emotion classifier Testing the model on your own image Source code

Summary

Optimizing TensorFlow Autoencoders

Introducing autoencoders Implementing an autoencoder

Source code for the autoencoder

Improving autoencoder robustness Building a denoising autoencoder

Source code for the denoising autoencoder

Convolutional autoencoders

Encoder Decoder Source code for convolutional autoencoder

Summary

Recurrent Neural Networks

RNNs basic concepts RNNs at work Unfolding an RNN The vanishing gradient problem LSTM networks An image classifier with RNNs

Source code for RNN image classifier

Bidirectional RNNs

Source code for the bidirectional RNN

Text prediction

Dataset Perplexity PTB model Running the example

Summary

GPU Computing

GPGPU computing GPGPU history The CUDA architecture GPU programming model TensorFlow GPU set up

Update TensorFlow

TensorFlow GPU management

Programming example

Source code for GPU computation

GPU memory management Assigning a single GPU on a multi-GPU system

Source code for GPU with soft placement

Using multiple GPUs

Source code for multiple GPUs management

Summary

Advanced TensorFlow Programming

Introducing Keras

Installation

Building deep learning models Sentiment classification of movie reviews

Source code for the Keras movie classifier

Adding a convolutional layer

Source code for movie classifier with convolutional layer

Pretty Tensor

Chaining layers

Normal mode Sequential mode Branch and join

Digit classifier

Source code for digit classifier

TFLearn

TFLearn installation

Titanic survival predictor

Source code for titanic classifier

Summary

Advanced Multimedia Programming with TensorFlow

Introduction to multimedia analysis Deep learning for Scalable Object Detection

Bottlenecks Using the retrained model

Accelerated Linear Algebra

Key strengths of TensorFlow Just-in-time compilation via XLA

JIT compilation Existence and advantages of XLA Under the hood working of XLA Still experimental Supported platforms More experimental material

TensorFlow and Keras

What is Keras? Effects of having Keras on board Video question answering system

Not runnable code!

Deep learning on Android

TensorFlow demo examples Getting started with Android

Architecture requirements Prebuilt APK Running the demo Building with Android studio Going deeper - Building with Bazel

Summary

Reinforcement Learning

Basic concepts of Reinforcement Learning Q-learning algorithm Introducing the OpenAI Gym framework FrozenLake-v0 implementation problem

Source code for the FrozenLake-v0 problem

Q-learning with TensorFlow Source code for the Q-learning neural network Summary

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