Practical MATLAB Deep Learning: A Projects-Based Approach

Contents
About the Authors
About the Technical Reviewer
Acknowledgments
Preface to the Second Edition
1 What Is Deep Learning?
	1.1 Deep Learning
	1.2 History of Deep Learning
	1.3 Neural Nets
		1.3.1 Daylight Detector
			Problem
			Solution
			How It Works
		1.3.2 XOR Neural Net
			Problem
			Solution
			How It Works
	1.4 Deep Learning and Data
	1.5 Types of Deep Learning
		1.5.1 Multi-layer Neural Network
		1.5.2 Convolutional Neural Network (CNN)
		1.5.3 Recurrent Neural Network (RNN)
		1.5.4 Long Short-Term Memory Network (LSTM)
		1.5.5 Recursive Neural Network
		1.5.6 Temporal Convolutional Machine (TCM)
		1.5.7 Stacked Autoencoders
		1.5.8 Extreme Learning Machine (ELM)
		1.5.9 Recursive Deep Learning
		1.5.10 Generative Deep Learning
		1.5.11 Reinforcement Learning
	1.6 Applications of Deep Learning
	1.7 Organization of the Book
2 MATLAB Toolboxes
	2.1 Commercial MATLAB Software
		2.1.1 MathWorks Products
			Deep Learning Toolbox
			Instrument Control Toolbox
			Statistics and Machine Learning Toolbox
			Computer Vision Toolbox
			Image Acquisition Toolbox
			Parallel Computing Toolbox
			Text Analytics Toolbox
	2.2 MATLAB Open Source
	2.3 XOR Example
	2.4 Training
	2.5 Zermelo's Problem
3 Finding Circles
	3.1 Introduction
	3.2 Structure
		3.2.1 imageInputLayer
		3.2.2 convolution2dLayer
		3.2.3 batchNormalizationLayer
		3.2.4 reluLayer
		3.2.5 maxPooling2dLayer
		3.2.6 fullyConnectedLayer
		3.2.7 softmaxLayer
		3.2.8 classificationLayer
		3.2.9 Structuring the Layers
	3.3 Generating Data
		3.3.1 Problem
		3.3.2 Solution
		3.3.3 How It Works
	3.4 Training and Testing
		3.4.1 Problem
		3.4.2 Solution
		3.4.3 How It Works
4 Classifying Movies
	4.1 Introduction
	4.2 Generating a Movie Database
		4.2.1 Problem
		4.2.2 Solution
		4.2.3 How It Works
	4.3 Generating a Viewer Database
		4.3.1 Problem
		4.3.2 Solution
		4.3.3 How It Works
	4.4 Training and Testing
		4.4.1 Problem
		4.4.2 Solution
		4.4.3 How It Works
5 Algorithmic Deep Learning
	5.1 Building the Filter
		5.1.1 Problem
		5.1.2 Solution
		5.1.3 How It Works
	5.2 Simulating
		5.2.1 Problem
		5.2.2 Solution
		5.2.3 How It Works
	5.3 Testing and Training
		5.3.1 Problem
		5.3.2 Solution
		5.3.3 How It Works
6 Tokamak Disruption Detection
	6.1 Introduction
	6.2 Numerical Model
		6.2.1 Dynamics
		6.2.2 Sensors
		6.2.3 Disturbances
		6.2.4 Controller
	6.3 Dynamical Model
		6.3.1 Problem
		6.3.2 Solution
		6.3.3 How It Works
	6.4 Simulate the Plasma
		6.4.1 Problem
		6.4.2 Solution
		6.4.3 How It Works
	6.5 Control the Plasma
		6.5.1 Problem
		6.5.2 Solution
		6.5.3 How It Works
	6.6 Training and Testing
		6.6.1 Problem
		6.6.2 Solution
		6.6.3 How It Works
7 Classifying a Pirouette
	7.1 Introduction
		7.1.1 Inertial Measurement Unit
		7.1.2 Physics
	7.2 Data Acquisition
		7.2.1 Problem
		7.2.2 Solution
		7.2.3 How It Works
	7.3 Orientation
		7.3.1 Problem
		7.3.2 Solution
		7.3.3 How It Works
	7.4 Dancer Simulation
		7.4.1 Problem
		7.4.2 Solution
		7.4.3 How It Works
	7.5 Real-Time Plotting
		7.5.1 Problem
		7.5.2 Solution
		7.5.3 How It Works
	7.6 Quaternion Display
		7.6.1 Problem
		7.6.2 Solution
		7.6.3 How It Works
	7.7 Making the IMU Belt
		7.7.1 Problem
		7.7.2 Solution
		7.7.3 How It Works
	7.8 Testing the System
		7.8.1 Problem
		7.8.2 Solution
		7.8.3 How It Works
	7.9 Classifying the Pirouette
		7.9.1 Problem
		7.9.2 Solution
		7.9.3 How It Works
	7.10 Data Acquisition GUI
		7.10.1 Problem
		7.10.2 Solution
		7.10.3 How It Works
	7.11 Hardware Sources
8 Completing Sentences
	8.1 Introduction
		8.1.1 Sentence Completion
		8.1.2 Grammar
		8.1.3 Sentence Completion by Pattern Recognition
		8.1.4 Sentence Generation
	8.2 Generating a Database
		8.2.1 Problem
		8.2.2 Solution
		8.2.3 How It Works
	8.3 Creating a Numeric Dictionary
		8.3.1 Problem
		8.3.2 Solution
		8.3.3 How It Works
	8.4 Mapping Sentences to Numbers
		8.4.1 Problem
		8.4.2 Solution
		8.4.3 How It Works
	8.5 Converting the Sentences
		8.5.1 Problem
		8.5.2 Solution
		8.5.3 How It Works
	8.6 Training and Testing
		8.6.1 Problem
		8.6.2 Solution
		8.6.3 How It Works
9 Terrain-Based Navigation
	9.1 Introduction
	9.2 Modeling Our Aircraft
		9.2.1 Problem
		9.2.2 Solution
		9.2.3 How It Works
	9.3 Generating Terrain
		9.3.1 Problem
		9.3.2 Solution
		9.3.3 How It Works
	9.4 Close-Up Terrain
		9.4.1 Problem
		9.4.2 Solution
		9.4.3 How It Works
	9.5 Building the Camera Model
		9.5.1 Problem
		9.5.2 Solution
		9.5.3 How It Works
	9.6 Plotting the Trajectory
		9.6.1 Problem
		9.6.2 Solution
		9.6.3 How It Works
	9.7 Creating the Training Images
		9.7.1 Problem
		9.7.2 Solution
		9.7.3 How It Works
	9.8 Training and Testing
		9.8.1 Problem
		9.8.2 Solution
		9.8.3 How It Works
	9.9 Simulation
		9.9.1 Problem
		9.9.2 Solution
		9.9.3 How It Works
10 Stock Prediction
	10.1 Introduction
	10.2 Generating a Stock Market
		10.2.1 Problem
		10.2.2 Solution
		10.2.3 How It Works
	10.3 Creating a Stock Market
		10.3.1 Problem
		10.3.2 Solution
		10.3.3 How It Works
	10.4 Training and Testing
		10.4.1 Problem
		10.4.2 Solution
		10.4.3 How It Works
11 Image Classification
	11.1 Introduction
	11.2 Using AlexNet
		11.2.1 Problem
		11.2.2 Solution
		11.2.3 How It Works
	11.3 Using GoogLeNet
		11.3.1 Problem
		11.3.2 Solution
		11.3.3 How It Works
12 Orbit Determination
	12.1 Introduction
	12.2 Generating the Orbits
		12.2.1 Problem
		12.2.2 Solution
		12.2.3 How It Works
	12.3 Training and Testing
		12.3.1 Problem
		12.3.2 Solution
		12.3.3 How It Works
	12.4 Implementing an LSTM
		12.4.1 Problem
		12.4.2 Solution
		12.4.3 How It Works
13 Earth Sensors
	13.1 Introduction
	13.2 Linear Output Earth Sensor
		13.2.1 Problem
		13.2.2 Solution
		13.2.3 How It Works
	13.3 Segmented Earth Sensor
		13.3.1 Problem
		13.3.2 Solution
		13.3.3 How It Works
	13.4 Linear Output Sensor Neural Network
		13.4.1 Problem
		13.4.2 Solution
		13.4.3 How It Works
	13.5 Segmented Sensor Neural Network
		13.5.1 Problem
		13.5.2 Solution
		13.5.3 How It Works
14 Generative Modeling of Music
	14.1 Introduction
	14.2 Generative Modeling Description
	14.3 Problem: Music Generation
	14.4 Solution
	14.5 Implementation
	14.6 Alternative Methods
15 Reinforcement Learning
	15.1 Introduction
	15.2 Titan Lander
	15.3 Titan Atmosphere
		15.3.1 Problem
		15.3.2 Solution
		15.3.3 How It Works
	15.4 Simulating the Aircraft
		15.4.1 Problem
		15.4.2 Solution
		15.4.3 How It Works
	15.5 Simulating Level Flight
		15.5.1 Problem
		15.5.2 Solution
		15.5.3 How It Works
	15.6 Optimal Trajectory
		15.6.1 Problem
		15.6.2 Solution
		15.6.3 How It Works
	15.7 Reinforcement Example
		15.7.1 Problem
		15.7.2 Solution
		15.7.3 How It Works
Bibliography
Index