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Verlag: Packt Publishing, Limited, 2017
ISBN 10: 1788397878ISBN 13: 9781788397872
Anbieter: Better World Books, Mishawaka, IN, USA
Buch
Zustand: Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.
Verlag: Packt Publishing - ebooks Account, 2017
ISBN 10: 1788397878ISBN 13: 9781788397872
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
Buch
Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Verlag: Packt Publishing, 2018
ISBN 10: 1789342090ISBN 13: 9781789342093
Anbieter: Buchpark, Trebbin, Deutschland
Buch
Zustand: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. | Seiten: 288.
Verlag: Packt Publishing, 2017
ISBN 10: 1788398432ISBN 13: 9781788398435
Anbieter: moluna, Greven, Deutschland
Buch
Zustand: New. Über den AutorGiuseppe 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 Bui.
Verlag: Packt Publishing Aug 2017, 2017
ISBN 10: 1788398432ISBN 13: 9781788398435
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Taschenbuch. Zustand: Neu. Neuware - Extract patterns and knowledge from your data in easy way using MATLABKey FeaturesGet your first steps into machine learning with the help of this easy-to-follow guideLearn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLABUnderstand how your data works and identify hidden layers in the data with the power of machine learning.Book DescriptionMATLAB 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.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.What you will learnLearn the introductory concepts of machine learning.Discover different ways to transform data using SAS XPORT, import and export toolsExplore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data.Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment.Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures.Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox.Learn feature selection and extraction for dimensionality reduction leading to improved performance.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.