We have recently updated our Privacy Policy. The site uses cookies to offer you a better experience. By continuing to browse the site you accept our Cookie Policy, you can change your settings at any time.

View Privacy PolicyView Cookie Policy
Visit our Christmas Gift Finder
MENU
SHOPS
SEARCH
0
Basket
 
Spend another £19.98 to qualify for free UK delivery.
Your order qualifies for free UK delivery.

Your basket is empty.

    • Books
This book can be found in:
Computing & Internet > Computer programming & software development > Web programming
Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)
  • Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)
zoom

Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)

(author), (author)
£39.99
Paperback 392 Pages / Published: 07/10/2016
  • In stock online
  • Free UK delivery

Usually dispatched within 24 hours

  • This item has been added to your basket
View basket Checkout
Your local Waterstones may have stock of this item. Please check by using Click & Collect
Synopsis
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 Muller 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

Publisher: O'Reilly Media, Inc, USA
ISBN: 9781449369415
Number of pages: 392
Weight: 590 g
Dimensions: 233 x 178 x 18 mm

You may also be interested in...

Fluent Python
Added to basket
Fluent Python
Luciano Ramalho
£39.99
Paperback
Programming Computer Vision with Python
Added to basket
Programming Computer Vision with Python
Jan Erik Solem
£39.99
Paperback
Ruby for Kids for Dummies
Added to basket
Ruby for Kids for Dummies
Christopher Haupt
£21.99
Paperback
Learning Python
Added to basket
Learning Python
Mark Lutz
£51.99
Paperback
The HTML Pocket Guide
Added to basket
The HTML Pocket Guide
Bruce Hyslop
£10.99
Paperback
Python Crash Course
Added to basket
Python Crash Course
Eric Matthes
£33.99
Paperback
JavaScript in Easy Steps
Added to basket
JavaScript in Easy Steps
Mike McGrath
£10.99
Paperback
Effective Python
Added to basket
Effective Python
Brett Slatkin
£29.49
Paperback
Python For Kids For Dummies
Added to basket
Python For Kids For Dummies
Brendan Scott
£21.99
Paperback
Learn Python the Hard Way
Added to basket
Learn Python the Hard Way
Zed A. Shaw
£29.48
Mixed media product
Learn Ruby the Hard Way
Added to basket
Learn Ruby the Hard Way
Zed A. Shaw
£29.48
Mixed media product
HTML and CSS
Added to basket
HTML and CSS
Jon Duckett
£31.99
Hardback

Reviews

Please sign in to write a review

Your review has been submitted successfully.