Data mining and algorithms
Data mining is the process of discovering predictive information from the analysis of large databases. For a data scientist, data mining can be a vague and daunting task – it requires a diverse set of skills and knowledge of many data mining techniques to take raw data and successfully get insights from it. You’ll want to understand the foundations of statistics, and different programming languages that can help you with data mining at scale.
This guide will provide an example-filled introduction to data mining using Python, one of the most widely used data mining tools – from cleaning and data organization to applying machine learning algorithms. First, let’s get a better understanding of data mining and how it is accomplished.
A data mining definition
The desired outcome from data mining is to create a model from a given dataset that can have its insights generalized to similar datasets. A real-world example of a successful data mining application can be seen in automatic fraud detection from banks and credit institutions.
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