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MATLAB machine learning [electronic resource]

MATLAB machine learning [electronic resource]

Material type
E-Book(소장)
Personal Author
Paluszek, Michael. Thomas, Stephanie.
Title Statement
MATLAB machine learning [electronic resource] / Michael Paluszek, Stephanie Thomas.
Publication, Distribution, etc
Berkeley, CA :   Apress,   c2017.  
Physical Medium
1 online resource (xix, 326 p.) : ill. (some col.).
기타형태 저록
Print version:   Paluszek, Michael.   MATLAB machine learning   9781484222492   (211009) 000045947766  
ISBN
9781484222492 9781484222508 (e-book)
요약
This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning Commercial and open source packages in MATLAB How to use MATLAB for programming and building machine learning applications MATLAB graphics for machine learning Practical real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.
General Note
Title from e-Book title page.  
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Machine learning.
Short cut
URL
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020 ▼a 9781484222492
020 ▼a 9781484222508 (e-book)
040 ▼a 211009 ▼c 211009 ▼d 211009
050 0 0 ▼a Q325.5 ▼b .P35 2017
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084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31
100 1 ▼a Paluszek, Michael.
245 1 0 ▼a MATLAB machine learning ▼h [electronic resource] / ▼c Michael Paluszek, Stephanie Thomas.
260 ▼a Berkeley, CA : ▼b Apress, ▼c c2017.
300 ▼a 1 online resource (xix, 326 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
520 ▼a This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It provides descriptions of all major areas in machine learning. The book reviews commercially available packages for machine learning and shows how they fit into the field. The book then shows how MATLAB can be used to solve machine learning problems and how MATLAB graphics can enhance the programmer’s understanding of the results and help users of their software grasp the results. Machine Learning can be very mathematical. The mathematics for each area is introduced in a clear and concise form so that even casual readers can understand the math. Readers from all areas of engineering will see connections to what they know and will learn new technology. The book then provides complete solutions in MATLAB for several important problems in machine learning including face identification, autonomous driving, and data classification. Full source code is provided for all of the examples and applications in the book. What you'll learn: An overview of the field of machine learning Commercial and open source packages in MATLAB How to use MATLAB for programming and building machine learning applications MATLAB graphics for machine learning Practical real world examples in MATLAB for major applications of machine learning in big data Who is this book for: The primary audiences are engineers and engineering students wanting a comprehensive and practical introduction to machine learning.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Machine learning.
700 1 ▼a Thomas, Stephanie.
776 0 8 ▼i Print version: ▼a Paluszek, Michael. ▼t MATLAB machine learning ▼z 9781484222492 ▼w (211009) 000045947766
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=https://doi.org/10.1007/978-1-4842-2250-8
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.31 Accession No. E14019036 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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