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✓ To learn about the concepts of data mining.
✓ To understand the need for, and the applications of data mining
✓ To differentiate between data mining and machine learning
✓ To understand the process of data mining.
✓ To understand the difference between data mining and machine learning.
Introduction to Data Mining
In the age of information, an enormous amount of data is available in different industries and organizations. The availability of this massive data is of no use unless it is transformed into valuable information. Otherwise, we are sinking in data, but starving for knowledge. The solution to this problem is data mining which is the extraction of useful information from the huge amount of data that is available.
Data mining is defined as follows:
‘Data mining is a collection of techniques for efficient automated discovery of previously unknown, valid, novel, useful and understandable patterns in large databases. The patterns must be actionable so they may be used in an enterprise's decision making.’
From this definition, the important take aways are:
Need of Data Mining
Data mining is a recent buzz word in the field of Computer Science. It is a computing process that uses intelligent mathematical algorithms to extract the relevant data and computes the probability of future actions. It is also known as Knowledge Discovery in Data (KDD).