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Practical Machine Learning

You're reading from   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

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Product type Paperback
Published in Jan 2016
Publisher Packt
ISBN-13 9781784399689
Length 468 pages
Edition 1st Edition
Languages
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Author (1):
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Sunila Gollapudi Sunila Gollapudi
Author Profile Icon Sunila Gollapudi
Sunila Gollapudi
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Toc

Table of Contents (16) Chapters Close

Preface 1. Introduction to Machine learning FREE CHAPTER 2. Machine learning and Large-scale datasets 3. An Introduction to Hadoop's Architecture and Ecosystem 4. Machine Learning Tools, Libraries, and Frameworks 5. Decision Tree based learning 6. Instance and Kernel Methods Based Learning 7. Association Rules based learning 8. Clustering based learning 9. Bayesian learning 10. Regression based learning 11. Deep learning 12. Reinforcement learning 13. Ensemble learning 14. New generation data architectures for Machine learning Index

Python


Python is one of the highly adopted programming or scripting languages in the field of Machine learning and data science. Python is always known for its ease of learning, implementation, and maintenance. Python is highly portable and can run on the Unix-based, Windows and Mac platforms. With the availability of libraries such as Pydoop and SciPy, its relevance in the world of big data analytics has tremendously increased.
Some of the key reasons for the popularity of Python in solving Machine learning problems are listed here:

  • Python is known to be well suited for data analysis

  • It is a versatile scripting language that can be used for writing some basic quick and dirty scripts for testing some basic functions, or it can be used in real-time applications leveraging its full-featured toolkits

  • Python comes with complete Machine learning packages (refer to http://mloss.org/software/) and can be used in a plug-and-play manner

Toolkit options in Python

Before we go deeper into what toolkit options...

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