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 6. Introducing the ML Package
In the previous chapter, we worked with the MLlib package in Spark that operated strictly on RDDs. In this chapter, we move to the ML part of Spark that operates strictly on DataFrames. Also, according to the Spark documentation, the primary machine learning API for Spark is now the DataFrame-based set of models contained in the spark.ml package.
So, let's get to it!
Note
In this chapter, we will reuse a portion of the dataset we played within the previous chapter. The data can be downloaded from http://www.tomdrabas.com/data/LearningPySpark/births_transformed.csv.gz.
In this chapter, you will learn how to do the following:
- Prepare transformers, estimators, and pipelines
- Predict the chances of infant survival using ...
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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.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.