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MATLAB for Machine Learning

You're reading from   MATLAB for Machine Learning Practical examples of regression, clustering and neural networks

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781788398435
Length 382 pages
Edition 1st Edition
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Authors (2):
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Pavan Kumar Kolluru Pavan Kumar Kolluru
Author Profile Icon Pavan Kumar Kolluru
Pavan Kumar Kolluru
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with MATLAB Machine Learning FREE CHAPTER 2. Importing and Organizing Data in MATLAB 3. From Data to Knowledge Discovery 4. Finding Relationships between Variables - Regression Techniques 5. Pattern Recognition through Classification Algorithms 6. Identifying Groups of Data Using Clustering Methods 7. Simulation of Human Thinking - Artificial Neural Networks 8. Improving the Performance of the Machine Learning Model - Dimensionality Reduction 9. Machine Learning in Practice

Preface

For humans, learning from mistakes is a fundamental rule. Why should it not be the same for machines? Machine learning algorithms will do just that: learn from experience. Machine learning gives computers the ability to learn without being explicitly programmed. It starts with real examples, extracts the models (that is, the rules that govern their operation), and uses them to make predictions about new examples.

MATLAB provides essential tools for understanding the amazing world of machine learning. Solving machine learning problems becomes extremely easy with the use of the tools available in the MATLAB environment. This is because MATLAB is a strong environment for interactive exploration.

For each topic, after a concise theoretical basis, you will be involved in real-life solutions. By the end of the book, you will be able to apply machine learning techniques and leverage the full capabilities of the MATLAB platform through real-world examples.

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