February 2017
Intermediate to advanced
274 pages
5h 58m
English
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Creating the final dataset
Therefore, it is time to create our final dataset that we will use to build our models. We will convert our DataFrame into an RDD of LabeledPoints.
A LabeledPoint is a MLlib structure that is used to train the machine learning models. It consists of two attributes: label and features.
The label is our target variable and features can be a NumPy array, list, pyspark.mllib.linalg.SparseVector, pyspark.mllib.linalg.DenseVector, or scipy.sparse column matrix.
Creating an RDD of LabeledPoints
Before we build our final dataset, we first need to deal with one final obstacle: our 'BIRTH_PLACE' feature is still a string. While any of the other categorical variables can be used as is (as they are now dummy variables), we will use ...
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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.