November 2016
Beginner to intermediate
941 pages
21h 55m
English
book
Python: Real World Machine Learning
by Prateek Joshi, John Hearty, Bastiaan Sjardin, Luca Massaron, Alberto Boschetti
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Machine learning with Spark
Here, we arrive at the main task of your job: creating a model to predict one or multiple attributes missing in the dataset. For this, we use some machine learning modeling, and Spark can provide us with a big hand in this context.
MLlib is the Spark machine learning library; although it is built in Scala and Java, its functions are also available in Python. It contains classification, regression, and recommendation learners, some routines for dimensionality reduction and feature selection, and has lots of functionalities for text processing. All of them are able to cope with huge datasets and use the power of all the nodes in the cluster to achieve the goal.
As of now (2016), it's composed of two main packages: mllib ...
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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.