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Index
Contents
About This Book
About The Author
Chapter 1: Introduction to Deep Learning
Introduction to Neural Networks
Biological Neurons
Deep Learning
Traditional Neural Networks versus Deep Learning
Building a Deep Neural Network
Demonstration 1: Loading and Modeling Data with Traditional Neural Network Methods
Demonstration 2: Building and Training Deep Learning Neural Networks Using CASL Code
Chapter 2: Convolutional Neural Networks
Introduction to Convoluted Neural Networks
Input Layers
Convolutional Layers
Using Filters
Padding
Feature Map Dimensions
Pooling Layers
Traditional Layers
Demonstration 1: Loading and Preparing Image Data
Demonstration 2: Building and Training a Convolutional Neural Network
Chapter 3: Improving Accuracy
Introduction
Architectural Design Strategies
Image Preprocessing and Data Enrichment
Transfer Learning Introduction
Domains and Subdomains
Types of Transfer Learning
Transfer Learning Biases
Transfer Learning Strategies
Customizations with FCMP
Tuning a Deep Learning Model
Chapter 4: Object Detection
Introduction
Types of Object Detection Algorithms
Data Preparation and Prediction Overview
Normalized Locations
Multi-Loss Error Function
Error Function Scalars
Anchor Boxes
Final Convolution Layer
Demonstration: Using DLPy to Access SAS Deep Learning Technologies: Part 1
Demonstration: Using DLPy to Access SAS Deep Learning Technologies: Part 2
Chapter 5: Computer Vision Case Study
References
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