Machine Learning Algorithms from Start to Finish in Python: Linear Regression. Probably one of the most common algorithms around, Linear Regression is a must know for Machine Learning Practitioners.
Probably one of the most common algorithms around, Linear Regression is a must know for Machine Learning Practitioners. This is usually a beginner’s first exposure to a real Machine Learning algorithm, and knowing how it operates on a deeper level is crucial to gain a better understanding of it.
So, briefly, let’s break down the real question; What really is Linear Regression?
Linear Regression is a supervised learning algorithm that aims at taking a linear approach at modelling the relation between a dependent variable and an independent variable. In other words, It aims to fit a linear trendline _that best captures the _relationship of the data, and, from this line, it can predict what the target values may be.
Great, I know the definition, but how does it really work? Great question! In order to answer the question, let’s run through a step by step process of how Linear Regression really operates:
This method of fitting a line is known as Least Squares.
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