Practical Machine Learning

Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials

Practical Machine Learning

Sunila Gollapudi

25 customer reviews
Learn how to build Machine Learning applications to solve real-world data analysis challenges with this Machine Learning book – packed with practical tutorials
Mapt Subscription
FREE
$40.00/m after trial
eBook
$10.00
RRP $37.99
Save 73%
Print + eBook
$46.99
RRP $46.99
What do I get with a Mapt subscription?
  • Unlimited access to all Packt’s 6,000+ eBooks and Videos
  • 100+ new titles a month, learning paths, assessments & code files
  • 1 Free eBook or Video to download and keep every month after trial
What do I get with an eBook?
  • Download this book in EPUB, PDF, MOBI formats
  • DRM FREE - read and interact with your content when you want, where you want, and how you want
  • Access this title in the subscription reader
What do I get with Print & eBook?
  • Get a paperback copy of the book delivered to you
  • Download this book in EPUB, PDF, MOBI formats
  • DRM FREE - read and interact with your content when you want, where you want, and how you want
  • Access this title in the subscription reader
What do I get with a Video?
  • Download this Video course in MP4 format
  • DRM FREE - read and interact with your content when you want, where you want, and how you want
  • Access this title in the subscription reader
$0.00
$10.00
$46.99
$29.99 p/m after trial
RRP $37.99
RRP $46.99
Subscription
eBook
Print + eBook
Start 14 Day Trial

Frequently bought together


Practical Machine Learning Book Cover
Practical Machine Learning
$ 37.99
$ 10.00
Python Machine Learning - Second Edition Book Cover
Python Machine Learning - Second Edition
$ 31.99
$ 10.00
Buy 2 for $20.00
Save $49.98
Add to Cart

Book Details

ISBN 139781784399689
Paperback468 pages

Book Description

This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data.

This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application.

With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data.

You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naïve Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.

Table of Contents

Chapter 5: Decision Tree based learning
Chapter 6: Instance and Kernel Methods Based Learning

What You Will Learn

  • Implement a wide range of algorithms and techniques for tackling complex data
  • Get to grips with some of the most powerful languages in data science, including R, Python, and Julia
  • Harness the capabilities of Spark and Hadoop to manage and process data successfully
  • Apply the appropriate machine learning technique to address real-world problems
  • Get acquainted with Deep learning and find out how neural networks are being used at the cutting-edge of machine learning
  • Explore the future of machine learning and dive deeper into polyglot persistence, semantic data, and more

Authors

Table of Contents

Chapter 5: Decision Tree based learning
Chapter 6: Instance and Kernel Methods Based Learning

Book Details

ISBN 139781784399689
Paperback468 pages
Read More
From 25 reviews

Read More Reviews

Recommended for You

Python Machine Learning - Second Edition Book Cover
Python Machine Learning - Second Edition
$ 31.99
$ 10.00
Machine Learning Algorithms Book Cover
Machine Learning Algorithms
$ 39.99
$ 10.00
Statistics for Machine Learning Book Cover
Statistics for Machine Learning
$ 39.99
$ 10.00
Mastering Machine Learning with scikit-learn - Second Edition Book Cover
Mastering Machine Learning with scikit-learn - Second Edition
$ 35.99
$ 10.00
Practical Data Science Cookbook - Second Edition Book Cover
Practical Data Science Cookbook - Second Edition
$ 35.99
$ 10.00
Principles of Data Science Book Cover
Principles of Data Science
$ 35.99
$ 10.00