Practical MATLAB Deep Learning:A Project-Based Approach
by:Michael Paluszek and Stephanie Thomas
pages 页数：252 pages
Publisher Finelybook 出版社：Apress; 1st ed. edition (February 8, 2020)
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB’s deep-learning toolboxes. You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning.
Along the way, you’ll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You’ll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You’ll also apply deep learning to aircraft navigation using images.
Finally, you’ll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB’s hardware capabilities.
What You Will Learn
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