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by Dan Van Boxel
Hands-On Deep Learning with TensorFlow
Hands-On Deep Learning with TensorFlow
Table of Contents
Hands-On Deep Learning with TensorFlow
Credits
About the Author
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Why subscribe?
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
1. Getting Started
Installing TensorFlow
TensorFlow – main page
TensorFlow – the installation page
Installing via pip
Installing via CoCalc
Simple computations
Defining scalars and tensors
Computations on tensors
Doing computation
Variable tensors
Viewing and substituting intermediate values
Logistic regression model building
Introducing the font classification dataset
Logistic regression
Getting data ready
Building a TensorFlow model
Logistic regression training
Developing the loss function
Training the model
Evaluating the model accuracy
Summary
2. Deep Neural Networks
Basic neural networks
Log function
Sigmoid function
Single hidden layer model
Exploring the single hidden layer model
Backpropagation
Single hidden layer explained
Understanding weights of the model
The multiple hidden layer model
Exploring the multiple hidden layer model
Results of the multiple hidden layer
Understanding the multiple hidden layers graph
Summary
3. Convolutional Neural Networks
Convolutional layer motivation
Multiple features extracted
Convolutional layer application
Exploring the convolution layer
Pooling layer motivation
Max pooling layers
Pooling layer application
Deep CNN
Adding convolutional and pooling layer combo
CNN to classify our fonts
Deeper CNN
Adding a layer to another layer of CNN
Wrapping up deep CNN
Summary
4. Introducing Recurrent Neural Networks
Exploring RNNs
Modeling the weights
Understanding RNNs
TensorFlow learn
Setup
Logistic regression
DNNs
Convolutional Neural Networks (CNNs) in Learn
Extracting weights
Summary
5. Wrapping Up
Research evaluation
A quick review of all the models
The logistic regression model
The single hidden layer neural network model
Deep neural network
Convolutional neural network
Deep convolutional neural network
The future of TensorFlow
Some more TensorFlow projects
Summary
Index
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