MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence

by Phil Kim

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 Who This Book Is For

Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

168 pages, Paperback

First published June 15, 2017

Reviews

[David Arrustico · Rating 1 out of 5]

Too basic. One could probably learn a lot more via moocs.

[Waleed El-Badry · Rating 4 out of 5]

The author succeeded to simplify the concept of neural network and deep learning using minimal theory and direct implementation. You would sail in the concept of what neural networks is all about, from shallow to deep learning passing by when to use activation functions and selection of cost functions. Each paradigm is supported with detailed steps and implementation using MATLAB.

What could add a great value to this book is using Neural Network toolbox for more advanced examples and case studies.

[Kristen Lancaster · Rating 4 out of 5]

Does not make use of the deep learning toolbox. Rather, this is an introduction to deep learning with Matlab being the language of choice for examples. Because Matlab so beautifully handles matrices, it is a good choice.

[Medhat ullah · Rating 4 out of 5]

Minimal theory implementation