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Data mining has become a buzzword today. It has become ubiquitous across numerous business sectors thanks to the potency of predictive data analytics & business process automation.
As a subject of study, data mining involves collecting, cleaning, processing, analyzing, and discovering insightful knowledge from data sets. A step-by-step roadmap comprising data collection, feature extraction & data cleaning & analytical processing, and algorithmic design defines all data mining processes. Different methods and techniques rely heavily upon statistical analyses and data manipulation using mathematics. And, therein lies the most significant difficulties of the domain.
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The biggest challenges associated with data mining stem from the nuances of myriad problem cases, the nature of different data types, and the intricate analytical techniques.
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Basic & Advanced Classification (Bayesian, decision tree, backpropagation, support vector machines, frequent patterns)
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