March 2019
Beginner to intermediate
182 pages
4h 6m
English
Content preview from Hands-On Big Data Analytics with PySpark
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Powerful Exploratory Data Analysis with MLlib
In this chapter, we will explore Spark's capability to perform regression tasks with models such as linear regression and support-vector machines (SVMs). We will learn how to compute summary statistics with MLlib, and discover correlations in datasets using Pearson and Spearman correlations. We will also test our hypothesis on large datasets.
We will cover the following topics:
- Computing summary statistics with MLlib
- Using the Pearson and Spearman methods to discover correlations
- Testing our hypotheses on large datasets
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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.