Practical MATLAB Deep Learning: A Project-Based Approach

Contents
About the Authors
About the Technical Reviewer
Acknowledgements
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 Multilayer Neural Network
		1.5.2 Convolutional Neural Networks (CNN)
		1.5.3 Recurrent Neural Network (RNN)
		1.5.4 Long Short-Term Memory Networks (LSTMs)
		1.5.5 Recursive Neural Network
		1.5.6 Temporal Convolutional Machines (TCMs)
		1.5.7 Stacked Autoencoders
		1.5.8 Extreme Learning Machine (ELM)
		1.5.9 Recursive Deep Learning
		1.5.10 Generative Deep Learning
	1.6 Applications of Deep Learning
	1.7 Organization of the Book
2
MATLAB Machine Learning Toolboxes
	2.1 Commercial MATLAB Software
		2.1.1 MathWorks Products
			Deep Learning Toolbox
			Instrument Control Toolbox
			Statistics and Machine Learning Toolbox
			Computer Vision System Toolbox
			Image Acquisition Toolbox
			Parallel Computing Toolbox
			Text Analytics Toolbox
	2.2 MATLAB Open Source
		2.2.1 Deep Learn Toolbox
		2.2.2 Deep Neural Network
		2.2.3 MatConvNet
		2.2.4 Pattern Recognition and Machine Learning Toolbox (PRMLT)
	2.3 XOR Example
	2.4 Training
	2.5 Zermelo\'s Problem
3
Finding Circles with Deep Learning
	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: Ellipses and Circles
		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 Movie Watcher 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 a Detection Filter
		5.1.1 Problem
		5.1.2 Solution
		5.1.3 How It Works
	5.2 Simulating Fault Detection
		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 Data Acquisition GUI
		7.7.1 Problem
		7.7.2 Solution
		7.7.3 How It Works
	7.8 Making the IMU Belt
		7.8.1 Problem
		7.8.2 Solution
		7.8.3 How It Works
	7.9 Testing the System
		7.9.1 Problem
		7.9.2 Solution
		7.9.3 How It Works
	7.10 Classifying the Pirouette
		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 of Sentences
		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 Map 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 a Terrain Model
		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 Plot Trajectory over an Image
		9.6.1 Problem
		9.6.2 Solution
		9.6.3 How It Works
	9.7 Creating the Test 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 Create 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 a Pretrained Network
		11.2.1 Problem
		11.2.2 Solution
		11.2.3 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
	12.5 Conic Sections
Bibliography
Index