Regression analysis is a core approach in the fields of machine learning and statistics. There are many type of regression analysis — logistic regression, linear regression, polynomial regression, etc. For this post we’ll be focusing on Linear Regression.
What is Regression?
Put simply, regression is a method for finding a relationship between (among) variables.
For example, you may have some data related to houses and their prices. Each house has features, like the number of rooms, number of floors, square footage, etc. Based on these features, prices of the houses vary.
The problem of predicting prices of the houses based on these features is a regression problem: the price is somehow related to the features described above. In regression analysis, you have a number of observations. Each observation has some features. By an assumption that some features are dependent upon others we try to establish a relationship among them.

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