logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) Machine Learning: The Art and Science of Algorithms that Make Sense of Data by Peter Flach ISBN 9781107096394, 9781107422223, 1107096391, 1107422221

  • SKU: EBN-4158066
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

0.0

0 reviews
Instant download (eBook) Machine Learning: The Art and Science of Algorithms that Make Sense of Data after payment.
Authors:Peter Flach
Pages:396 pages.
Year:2012
Editon:1st
Publisher:Cambridge University Press
Language:english
File Size:6.78 MB
Format:pdf
ISBNS:9781107096394, 9781107422223, 1107096391, 1107422221
Categories: Ebooks

Product desciption

(Ebook) Machine Learning: The Art and Science of Algorithms that Make Sense of Data by Peter Flach ISBN 9781107096394, 9781107422223, 1107096391, 1107422221

As one of the most comprehensive machine learning texts around, this book does justice to the field’s incredible richness, but without losing sight of the unifying principles. Peter Flach’s clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. He covers a wide range of logical, geometric and statistical models, and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features.

Machine Learning will set a new standard as an introductory textbook:

• The Prologue and Chapter 1 are freely available on-line, providing an accessible first step into machine learning.

• The use of established terminology is balanced with the introduction of new and useful concepts.

• Well-chosen examples and illustrations form an integral part of the text.

• Boxes summarise relevant background material and provide pointers for revision. Each chapter concludes with a summary and suggestions for further reading.

• A list of "Important points to remember" is included at the back of the book together with an extensive index to help readers navigate through the material.

*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products