February 2017
Intermediate to advanced
274 pages
5h 58m
English
Content preview from Learning PySparkBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 5. Introducing MLlib
In the previous chapter, we learned how to prepare the data for modeling. In this chapter, we will actually use some of that learning to build a classification model using the MLlib package of PySpark.
MLlib stands for Machine Learning Library. Even though MLlib is now in a maintenance mode, that is, it is not actively being developed (and will most likely be deprecated later), it is warranted that we cover at least some of the features of the library. In addition, MLlib is currently the only library that supports training models for streaming.
Note
Starting with Spark 2.0, ML is the main machine learning library that operates on DataFrames instead of RDDs as is the case for MLlib.
The documentation for MLlib can be found ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.