Practical MATLAB Deep Learning, Second Edition

Our latest textbook on MATLAB programming is now available from Apress. Practical MATLAB Deep Learning, A Projects-Based Approach, is in its second edition. It is available in both electronic and hard copy from SpringerLink.

New coauthor Eric Ham, a deep learning research specialist, joins Michael Paluszek and Stephanie Thomas. Mr. Ham led the development of a new chapter on generative modeling of music.

The software is available from GitHub:

About the Book

Harness the power of MATLAB for deep-learning challenges. Practical MATLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MATLAB’s deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. This edition includes new and expanded projects, and covers generative deep learning and reinforcement learning.

Over the course of the book, you’ll learn to model complex systems and apply deep learning to problems in those areas. Applications include:

  • NEW: An aircraft that lands on Titan, the moon of Saturn, using reinforcement learning
  • NEW: Music creation using generative deep learning
  • NEW: Earth sensor processing for spacecraft
  • Aircraft navigation
  • MATLAB Bluetooth data acquisition applied to dance physics
  • Stock market prediction
  • Natural language processing
  • Plasma control

 You will:

  • Explore deep learning using MATLAB and compare it to algorithms
  • Write a deep learning function in MATLAB and train it with examples
  • Use MATLAB toolboxes related to deep learning
  • Implement tokamak disruption prediction

The book primarily features the Deep Learning Toolbox and the Reinforcement Learning toolboxes. Some examples in the book feature other MathWorks toolboxes, include the Instrument Control toolbox, Optimization toolbox, Statistics and Machine Learning, and Image Processing toolbox.

Our other books

This new second edition joins our other books available from Apress:

eBook Textbook now available on Barnes & Noble

Our aerospace theory textbook, Spacecraft Attitude and Orbit Control, has been included with purchases of the Spacecraft Control Toolbox for years and available for purchase as a standalone PDF. We have now compiled our book as an eBook and it is available from Barnes and Noble for Nook:

The companion tutorial software for the book (Chapter 2) is available for download from our website.

Machine Learning Recipes: 2nd Edition

Apress has released a second edition of our textbook, MATLAB Machine Learning Recipes! New chapters include Fuzzy Logic and Expert Systems. We have also expanded our discussions of Neural Networks and Multiple Hypothesis Testing. The book provides a broad overview of machine learning including topics from adaptive control and estimation. Examples include learning control of aircraft and automobile target tracking.

Our book is available from Amazon or directly from Apress!

The software is available on GitHub:, or you can download it from our support site:

The software is packaged as a MATLAB toolbox, so it is easy to install and uninstall!

Brand New Free SCT Textbook Companion App for MATLAB

We are happy to announce the release of our free Textbook Companion App for MATLAB (2012b or later).  Based on four Chapter 2 walk through tutorials, the goal is to design a geostationary spacecraft, maintaining an exact orbital position, delivering a -126 dB in the Ku band, and 7 year lifetime.


The GUI allows us to look at the results of various gravity models, summing various types of disturbances caused by the sun-angle, a basic geo-synchronous orbit simulation, and then a full simulation that incorporates the orbit, disturbances, and Control and Link parameters. app_results

The app is available on the textbook support page: