The book then moves on to data cleansing, mining, and analyzing various data types in machine learning and the reader will see how to display data values on a plot. Next, the reader will learn about the different types of regression techniques and how to apply them to their data using the MATLAB functions. The reader will understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, the book explores feature selection and extraction techniques for dimensionality reduction for performance improvement.
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We use cookies to give you the best possible experience. By using our website you agree to our use of cookies. Dispatched from the UK in 3 business days When will my order arrive? Home Contact us Help Free delivery worldwide. Free delivery worldwide. Bestselling Series. Harry Potter. Popular Features. Home Learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications.
A mathematical and statistical background will really help in following this book well. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot.
Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement.
At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work. Product details Format Paperback pages Dimensions x x He has over 15 years of work experience in programming, first in the field of combustion and then in acoustics and noise control.
An expert in acoustics and noise control, Giuseppe has wide experience in teaching professional computer courses about 15 years , dealing with e-learning as an author. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He is currently researching machine learning applications in acoustics and noise control.
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