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) Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Müller, Sarah Guido ISBN 9781449369415, 1449369413

  • SKU: EBN-35139178
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.3

30 reviews
Instant download (eBook) Introduction to Machine Learning with Python: A Guide for Data Scientists after payment.
Authors:Andreas C. Müller, Sarah Guido
Pages:376 pages.
Year:2016
Editon:1
Publisher:O'Reilly Media
Language:english
File Size:5.84 MB
Format:pdf
ISBNS:9781449369415, 1449369413
Categories: Ebooks

Product desciption

(Ebook) Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Müller, Sarah Guido ISBN 9781449369415, 1449369413

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products