MATLAB machine learning recipes : a problem-solution approach

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable....

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Bibliographic Details
Main Authors Paluszek, Michael (Author), Thomas, Stephanie (Educator) (Author)
Format Electronic eBook
LanguageEnglish
Published New York : Apress, [2019]
EditionSecond edition.
Subjects
MATLAB.
MATLAB
Machine learning.
elektronické knihy
electronic books
Online AccessFull text
ISBN9781484239162
1484239164
9781484252413
1484252411
9781484239155
1484239156
9781484239179
1484239172
Physical Description1 online resource : illustrations

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100 1 |a Paluszek, Michael,  |e author. 
245 1 0 |a MATLAB machine learning recipes :  |b a problem-solution approach /  |c Michael Paluszek and Stephanie Thomas. 
250 |a Second edition. 
264 1 |a New York :  |b Apress,  |c [2019] 
264 4 |c ©2019 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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504 |a Includes bibliographical references and index. 
505 0 |a Introduction -- An overview of machine learning -- Representation of data for machine learning in MATLAB -- MATLAB graphics -- Kalman filters -- Adaptive control -- Fuzzy logic -- Data classification with decision trees -- Introduction to neural nets -- Classification of numbers using neural networks -- Pattern recognition with deep learning -- Neural aircraft control -- Multiple hypothesis testing -- Autonomous driving with multiple hypothesis testing -- Case-based expert systems -- A brief history of autonomous learning -- Software for machine learning. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem. All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable. The toolbox that the code uses provides a complete set of functions needed to implement all aspects of machine learning. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow the reader to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. You will: Learn to write code for machine learning, adaptive control and estimation using MATLAB See how these three areas complement each other Understand why these three areas are needed for robust machine learning applications Use MATLAB graphics and visualization tools for machine learning Code real world examples in MATLAB for major applications of machine learning in big data. 
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700 1 |a Thomas, Stephanie  |c (Educator),  |e author.  |1 https://id.oclc.org/worldcat/entity/E39PCjBG3VHy3B8vJkjxGxBtrq 
776 0 8 |i Printed edition:  |z 9781484239155 
776 0 8 |i Printed edition:  |z 9781484239179 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpMATLABMM/matlab-machine-learning?kpromoter=marc  |y Full text 

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