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Index
Title Page Copyright
TensorFlow 1.x Deep Learning Cookbook
Credits About the Authors About the Reviewers www.PacktPub.com
Why subscribe?
Customer Feedback Dedication Preface
What this book covers What you need for this book Who this book is for Sections
Getting ready How to do it… How it works… There's more… See also
Conventions Reader feedback Customer support
Downloading the example code Errata Piracy Questions
TensorFlow - An Introduction
Introduction Installing TensorFlow
Getting ready How to do it... How it works... There's more...
Hello world in TensorFlow
How to do it... How it works...
Understanding the TensorFlow program structure
How to do it... How it works... There's more...
Working with constants, variables, and placeholders
How to do it... How it works... There's more...
Performing matrix manipulations using TensorFlow
How to do it... How it works... There's more...
Using a data flow graph
How to do it...
Migrating from 0.x to 1.x
How to do it... There's more...
Using XLA to enhance computational performance
Getting ready How to do it...
Invoking CPU/GPU devices
How to do it... How it works...
TensorFlow for Deep Learning
How to do it... There's more
Different Python packages required for DNN-based problems
How to do it... See also
Regression
Introduction Choosing loss functions
Getting ready  How to do it... How it works... There's more...
Optimizers in TensorFlow
Getting ready How to do it... There's more... See also
Reading from CSV files and preprocessing data
Getting ready How to do it… There's more...
House price estimation-simple linear regression
Getting ready How to do it... How it works... There's more...
House price estimation-multiple linear regression
How to do it... How it works... There's more...
Logistic regression on the MNIST dataset
How to do it... How it works... See also
Neural Networks - Perceptron
Introduction Activation functions
Getting ready How to do it... How it works... There's more... See also
Single layer perceptron
Getting ready How to do it... There's more...
Calculating gradients of backpropagation algorithm 
Getting ready How to do it... How it works... There's more... See also
MNIST classifier using MLP
Getting ready How to do it... How it works...
Function approximation using MLP-predicting Boston house prices
Getting ready How to do it... How it works... There's more...
Tuning hyperparameters
How to do it... There's more... See also
Higher-level APIs-Keras
How to do it... There's more...
See also
Convolutional Neural Networks
Introduction
Local receptive fields Shared weights and bias A mathematical example ConvNets in TensorFlow Pooling layers Max pooling Average pooling ConvNets summary
Creating a ConvNet to classify handwritten MNIST numbers
Getting ready How to do it... How it works...
Creating a ConvNet to classify CIFAR-10
Getting ready How to do it... How it works... There's more...
Transferring style with VGG19 for image repainting
Getting ready How to do it... How it works... There's more...
Using a pretrained VGG16 net for transfer learning
Getting ready How to do it... How it works... There's more...
Creating a DeepDream network
Getting ready How to do it... How it works... There's more... See also
Advanced Convolutional Neural Networks
Introduction Creating a ConvNet for Sentiment Analysis
Getting ready How to do it... How it works... There is more...
Inspecting what filters a VGG pre-built network has learned
Getting ready How to do it... How it works... There is more...
Classifying images with VGGNet, ResNet, Inception, and Xception
VGG16 and VGG19 ResNet Inception Xception Getting ready How to do it... How it works... There is more...
Recycling pre-built Deep Learning models for extracting features
Getting ready How to do it... How it works...
Very deep InceptionV3 Net used for Transfer Learning
Getting ready How to do it... How it works... There is more...
Generating music with dilated ConvNets, WaveNet, and NSynth
Getting ready How to do it... How it works... There is more...
Answering questions about images (Visual Q&A)
How to do it... How it works... There is more...
Classifying videos with pre-trained nets in six different ways
How to do it... How it works... There is more...
Recurrent Neural Networks
Introduction
Vanishing and exploding gradients Long Short Term Memory (LSTM) Gated Recurrent Units (GRUs) and Peephole LSTM Operating on sequences of vectors
Neural machine translation - training a seq2seq RNN
Getting ready How to do it... How it works...
Neural machine translation - inference on a seq2seq RNN
How to do it... How it works...
All you need is attention - another example of a seq2seq RNN
How to do it... How it works... There's more...
Learning to write as Shakespeare with RNNs
How to do it... How it works...
First iteration After a few iterations
There's more...
Learning to predict future Bitcoin value with RNNs
How to do it... How it works... There's more...
Many-to-one and many-to-many RNN examples
How to do it... How it works...
Unsupervised Learning
Introduction Principal component analysis
Getting ready How to do it... How it works... There's more... See also
k-means clustering
Getting ready How to do it... How it works... There's more... See also
Self-organizing maps
Getting ready How to do it... How it works... See also
Restricted Boltzmann Machine
Getting ready How to do it... How it works... See also
Recommender system using RBM
Getting ready How to do it... There's more...
DBN for Emotion Detection
Getting ready How to do it... How it works... There's more...
Autoencoders
Introduction
See Also
Vanilla autoencoders
Getting ready How to do it... How it works... There's more...
Sparse autoencoder
Getting Ready... How to do it... How it works... There's More... See Also
Denoising autoencoder
Getting Ready How to do it... See Also
Convolutional autoencoders
Getting Ready... How to do it... How it Works... There's More... See Also
Stacked autoencoder
Getting Ready How to do it... How it works... There's More... See Also
Reinforcement Learning
Introduction Learning OpenAI Gym
Getting ready How to do it... How it works... There's more... See also
Implementing neural network agent to play Pac-Man
Getting ready How to do it...
Q learning to balance Cart-Pole
Getting ready How to do it... There's more... See also
Game of Atari using Deep Q Networks
Getting ready How to do it... There's more... See also
Policy gradients to play the game of Pong
Getting ready How to do it... How it works... There's more...
AlphaGo Zero
See also
Mobile Computation
Introduction
TensorFlow, mobile, and the cloud
Installing TensorFlow mobile for macOS and Android
Getting ready How to do it... How it works... There's more...
Playing with TensorFlow and Android examples
Getting ready How to do it... How it works...
Installing TensorFlow mobile for macOS and iPhone
Getting ready How to do it... How it works... There's more...
Optimizing a TensorFlow graph for mobile devices
Getting ready How to do it... How it works...
Profiling a TensorFlow graph for mobile devices
Getting ready How to do it... How it works...
Transforming a TensorFlow graph for mobile devices
Getting ready How to do it... How it works...
Generative Models and CapsNet
Introduction
So what is a GAN? Some cool GAN applications
Learning to forge MNIST images with simple GANs
Getting ready How to do it... How it works...
Learning to forge MNIST images with DCGANs
Getting ready How to do it... How it works...
Learning to forge Celebrity Faces and other datasets with DCGAN
Getting ready How to do it... How it works... There's more...
Implementing Variational Autoencoders
Getting ready... How to do it... How it works... There's More... See also...
Learning to beat the previous MNIST state-of-the-art results with Capsule Networks
Getting ready How to do it... How it works... There's more...
Distributed TensorFlow and Cloud Deep Learning
Introduction Working with TensorFlow and GPUs
Getting ready How to do it... How it works...
Playing with Distributed TensorFlow: multiple GPUs and one CPU
Getting ready How to do it... How it works...
Playing with Distributed TensorFlow: multiple servers
Getting ready How to do it... How it works... There is more...
Training a Distributed TensorFlow MNIST classifier
Getting ready How to do it... How it works...
Working with TensorFlow Serving and Docker
Getting ready How to do it... How it works... There is more...
Running Distributed TensorFlow on Google Cloud (GCP) with Compute Engine
Getting ready How to do it... How it works... There is more...
Running Distributed TensorFlow on Google CloudML
Getting ready How to do it... How it works... There is more...
Running Distributed TensorFlow on Microsoft Azure
Getting ready How to do it... How it works... There's more...
Running Distributed TensorFlow on Amazon AWS
Getting ready How to do it... How it works... There is more...
Learning to Learn with AutoML (Meta-Learning)
Meta-learning with recurrent networks and with reinforcement learning Meta-learning blocks Meta-learning novel tasks Siamese Network
Applications of Siamese Networks A working example - MNIST
TensorFlow Processing Units
Components of TPUs
Advantages of TPUs Accessing TPUs Resources on TPUs
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