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A Logistic Regression classifies observations by estimating the probability that an observation is in a particular category.

Naive Bayes is a probabilistic classification method based on the Bayes Theorem. In general, the Bayes Theorem gives the relationship between the probabilities of two events and their conditional probability.

Linear Regression is an analytical technique used to model the relationship between several input variables and a continuous outcome variable.

Decision Trees is a type of Supervised Algorithm, which uses a tree structure to specify sequences of decisions and consequences, for a given input X,

In this blog, I will be explaining about how to further clean the technical data into a ‘Consistent Data’ and the methodologies adopted.

Data Cleaning is the process of transforming raw data into consistent data that can be analyzed.