Overview
- Demonstrates how to counter real world problems found in big data, smart bots and more through practical examples
- Broadens your understanding of neural networks, deep learning, and convolutional neural networks
- Explains how to use MATLAB for deep learning
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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.
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.
Similar content being viewed by others
Table of contents (6 chapters)
Authors and Affiliations
About the author
Phil Kim, PhD is an experienced MATLAB programmer and user. He also works with algorithms of large data sets drawn from AI, machine learning. He has worked at Korea Aerospace Research Institute as a Senior Researcher. There, his main task was to develop autonomous flight algorithm and onboard software for unmanned aerial vehicle. An on-screen keyboard program named 'Clickey' was developed by him during his period in PhD program and served as a bridge to bring the author currently to his current assignment as a Senior Research Officer at National Rehabilitation Research Institute of Korea.
Accessibility Information
Accessibility information for this book is coming soon. We're working to make it available as quickly as possible. Thank you for your patience.
Bibliographic Information
Book Title: MATLAB Deep Learning
Book Subtitle: With Machine Learning, Neural Networks and Artificial Intelligence
Authors: Phil Kim
DOI: https://doi.org/10.1007/978-1-4842-2845-6
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Phil Kim 2017
Softcover ISBN: 978-1-4842-2844-9Published: 15 June 2017
eBook ISBN: 978-1-4842-2845-6Published: 15 June 2017
Edition Number: 1
Number of Pages: XVII, 151
Number of Illustrations: 75 b/w illustrations, 20 illustrations in colour
Topics: Big Data, Artificial Intelligence, Mathematical Logic and Formal Languages, Programming Languages, Compilers, Interpreters, Programming Techniques