logo

EbookBell.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://ebookbell.com/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.

EbookBell Team

An Introduction To Machine Learning 2nd Edition Miroslav Kubat

  • SKU: BELL-6687484
An Introduction To Machine Learning 2nd Edition Miroslav Kubat
$ 31.00 $ 45.00 (-31%)

4.0

46 reviews

An Introduction To Machine Learning 2nd Edition Miroslav Kubat instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 3.04 MB
Pages: 291
Author: Miroslav Kubat
ISBN: 9783319639123, 9783319639130, 3319639129, 3319639137
Language: English
Year: 2017
Edition: 2

Product desciption

An Introduction To Machine Learning 2nd Edition Miroslav Kubat by Miroslav Kubat 9783319639123, 9783319639130, 3319639129, 3319639137 instant download after payment.

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting,” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms.

Related Products