{"product_id":"matlab-for-machine-learning-practical-examples-of-regression-clustering-and-neural-networks-9781788398435","title":"MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks","description":"\u003cp\u003e\u003cstrong\u003eExtract patterns and knowledge from your data in easy way using MATLAB\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eGet your first steps into machine learning with the help of this easy-to-follow guide\u003c\/li\u003e\n\u003cli\u003eLearn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB\u003c\/li\u003e\n\u003cli\u003eUnderstand how your data works and identify hidden layers in the data with the power of machine learning.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eMATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eYou'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.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eYou'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.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAt 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.\u003c\/p\u003e\u003cp\u003e \u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eLearn the introductory concepts of machine learning.\u003c\/li\u003e\n\u003cli\u003eDiscover different ways to transform data using SAS XPORT, import and export tools, \u003c\/li\u003e\n\u003cli\u003eExplore the different types of regression techniques such as simple \u0026amp; multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data.\u003c\/li\u003e\n\u003cli\u003eDiscover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment.\u003c\/li\u003e\n\u003cli\u003eUncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures.\u003c\/li\u003e\n\u003cli\u003eKnow how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox.\u003c\/li\u003e\n\u003cli\u003eLearn feature selection and extraction for dimensionality reduction leading to improved performance.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eThis 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.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003eCiaburro, Giuseppe:\u003c\/i\u003e\u003c\/b\u003e - Giuseppe Ciaburro holds a PhD in environmental technical physics, along with two master's degrees. His research was focused on machine learning applications in the study of urban sound environments. He works at the Built Environment Control Laboratory at the Università degli Studi della Campania Luigi Vanvitelli, Italy. He has over 15 years' professional experience in programming (Python, R, and MATLAB), first in the field of combustion, and then in acoustics and noise control. He has several publications to his credit.","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50363171012882,"sku":"9781788398435","price":50.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_3650db00-8339-417f-b453-3cbeaaeca630.jpg?v=1728406905","url":"https:\/\/surprise-castle.myshopify.com\/products\/matlab-for-machine-learning-practical-examples-of-regression-clustering-and-neural-networks-9781788398435","provider":"Surprise Castle","version":"1.0","type":"link"}