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Hands-On Data Science and Python Machine Learning

You're reading from   Hands-On Data Science and Python Machine Learning Perform data mining and machine learning efficiently using Python and Spark

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787280748
Length 420 pages
Edition 1st Edition
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Author (1):
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Frank Kane Frank Kane
Author Profile Icon Frank Kane
Frank Kane
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Table of Contents (11) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Statistics and Probability Refresher, and Python Practice 3. Matplotlib and Advanced Probability Concepts 4. Predictive Models 5. Machine Learning with Python 6. Recommender Systems 7. More Data Mining and Machine Learning Techniques 8. Dealing with Real-World Data 9. Apache Spark - Machine Learning on Big Data 10. Testing and Experimental Design

Decision Trees in Spark with MLlib

Alright, let's actually build some decision trees using Spark and the MLlib library, this is very cool stuff. Wherever you put the course materials for this book, I want you to go to that folder now. Make sure you're completely closed out of Canopy, or whatever environment you're using for Python development, because I want to make sure you're starting it from this directory, OK? And find the SparkDecisionTree script, and double-click that to open up Canopy:

Now, up until this point we've been using IPython notebooks for our code, but you can't really use those very well with Spark. With Spark scripts, you need to actually submit them to the Spark infrastructure and run them in a very special way, and we'll see how that works shortly.

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