Practical MATLAB deep learning : a project-based approach
著者
書誌事項
Practical MATLAB deep learning : a project-based approach
Apress , Springer Science+Business Media [Distributor], c2020
- : pbk
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注記
Includes bibliographical references (p. 247-248) and index
内容説明・目次
内容説明
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
Who This Book Is For
Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
目次
1 What is Deep Learning?2 MATLAB Machine and Deep Learning Toolboxes3 Finding Circles with Deep Learning4 Classifying Movies5 Algorithmic Deep Learning6 Tokamak Disruption Detection7 Classifying a Pirouette8 Completing Sentences9 Terrain Based Navigation10 Stock Prediction11 Image Classification12 Orbit Determination
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