This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.
Table of Contents
Chapter 1: Introduction to Visual Computing
Chapter 2: Learning As a Regression Problem
Chapter 3: Artificial Neural Networks
Chapter 4: Convolutional Neural Networks
Chapter 5: Modern and Novel Usages of CNNs