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Building a Recommendation Engine with Scala by Saleem Ansari

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Extraction and transformation for machine learning

To properly extract and transform the data, we need to first understand what kind of data we are dealing with, only then we can proceed with cleaning it. Now we will discuss in brief, the different kinds of data that are usually encountered in practice.

Types of data

To apply any algorithm to a dataset, we first need to map the data to a machine readable form. Let's discuss what kinds of basic features we will find in any dataset. There are three broad categories in which we can segregate the features: discreet, continuous, and categorical.

Discrete

The word discrete means separate and distinct, which essentially captures the essence of discreet features. Therefore, discrete simply means something ...

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