January 2018
Intermediate to advanced
470 pages
11h 9m
English
Content preview from Scala Machine Learning Projects
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Exploratory analysis of the dataset
Let's look at some data properties (use the EDA.scala file for this). At first, we need to read the training set to see the available properties. To begin with, let's place your training set in your project directory or somewhere else and point to it accordingly:
val train = "data/insurance_train.csv"
I hope you have Java, Scala and Spark installed and configured on your machine. If not, please do so. Anyway, I'm assuming they are. So let's create an active Spark session, which is the gateway for any Spark application:
val spark = SparkSessionCreate.createSession()import spark.implicits._
Spark session alias on Scala REPL:
If you are inside Scala REPL, the Spark session alias spark is already defined, so ...
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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.