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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

From Data to Knowledge Discovery

Modern computer technology, coupled with the availability of more and more powerful sensors, has led to impressive-sized collections of information. Having a lot of data, on one hand, undoubtedly represents an advantage; on the other hand, it is a problem. This is because it imposes obvious management problems, in the sense that more sophisticated tools will be needed to extract knowledge from it.

These pieces of data, taken individually, are in fact pieces of elementary information that describe some particular aspects of a phenomenon, but do not allow us to represent them. To get more knowledge about a phenomenon, a form of analysis is needed that can link the data to some significant aspect of the phenomenon itself. It is therefore necessary to follow a path to transform data into an element of knowledge.

The two important steps in this path...

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