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Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem.
All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more.
What you'll learn:
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How to write code for machine learning, adaptive control and estimation using MATLAB
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How these three areas complement each other
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How these three areas are needed for robust machine learning applications
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How to use MATLAB graphics and visualization tools for machine learning
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How to code real world examples in MATLAB for major applications of machine learning in big data
Who is this book for:
The primary audiences are engineers, data scientists and students wanting a comprehensive and code cookbook rich in examples on machine learning using MATLAB.
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AdvancED Game Design with Flash
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This book gives graphic designers the confidence to do everything necessary to ensure trouble-free, high-qualityprintingto calibrate images; adjust trapping levels; and mix colors that wont print as something that is a complete surprise. It explains scanning and resolution, and discusses good and bad image formats, describing techniques to... | | Web Based Learning: A Practical GuideThe premise on which this title is based is: "To be successful in integrating technology into classroom instruction, training for teachers must first focus on effective lesson plan design and teaching strategies. Without mastering these skills first, no amount of technical training, no matter how effective, will translate into valuable... |
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