MATLAB Deep Learning
Author | : Phil Kim |
Publisher | : Apress |
Total Pages | : 162 |
Release | : 2017-06-15 |
ISBN-10 | : 9781484228456 |
ISBN-13 | : 1484228456 |
Rating | : 4/5 (456 Downloads) |
Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.