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MATLAB for Machine Learning

MATLAB for Machine Learning

By : Giuseppe Ciaburro
4.8 (4)
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MATLAB for Machine Learning

MATLAB for Machine Learning

4.8 (4)
By: Giuseppe Ciaburro

Overview of this book

Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications. By navigating the versatile machine learning tools in the MATLAB environment, you’ll learn how to seamlessly interact with the workspace. You’ll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you’ll explore various classification and regression techniques, skillfully applying them with MATLAB functions. This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You’ll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you’ll leverage MATLAB tools for deep learning and managing convolutional neural networks. By the end of the book, you’ll be able to put it all together by applying major machine learning algorithms in real-world scenarios.
Table of Contents (17 chapters)
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1
Part 1: Getting Started with Matlab
4
Part 2: Understanding Machine Learning Algorithms in MATLAB
9
Part 3: Machine Learning in Practice

Working with different types of data

Working with different types of data involves understanding their specific formats and applying appropriate techniques for manipulation and analysis. Here are some common types of data and general considerations for working with them.

Working with images

In MATLAB, working with images involves loading, displaying, and performing various operations on image data. Here’s a brief overview of how to work with images in MATLAB:

  • Loading an image: We can load an image into MATLAB using the imread() function. It reads the image file and returns a numeric array representing the image data. Here’s an example:
    img = imread('coliseum.jpg');
  • Displaying an image: MATLAB provides the imshow() function to display an image. It opens a separate window and shows the image. Here’s an example:
    imshow(img);
  • Manipulating an image: MATLAB offers a wide range of functions to perform various operations on images. For example...

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