Convolutional Neural Networks in Visual Computing: A Concise Guide

by Ragav Venkatesan, Baoxin Li

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.

168 pages, Paperback

Published September 22, 2017

Reviews

[Brent · Rating 5 out of 5]

This book does a great job at explaining a lot of the basic machine learning (ML) techniques and helps the reader understand their pitfalls. If you are starting out in ML and are interesting in deep learning, then I would suggest checking out this book.