Linear regression is a fundamental algorithm used in machine learning and statistics. It's a supervised learning method, meaning it learns from data that is already labeled. This data consists of an independent variable (usually on the X-axis) and a dependent variable (usually on the Y-axis). The goal of linear regression is to find the relationship between these variables and use that relationship to predict the value of the dependent variable for new data points.

This Linear Regression Tutorial by Great Learning would help you to comprehensively learn all the underlying concepts of Linear Regression.

This session will be taken by Professor Mukesh Rao, who is the academic director at Great Learning. Professor Mukesh Rao has over 20 years of industry experience in Market Research, Project Management, and Data Science.

The following topics are covered in the session:
* Introduction - 00:00:00
* Case Study to understand the need of Linear Regression - 00:01:12
* Introduction to Linear Regression - 00:04:18
* Introduction to Multiple Linear Regression - 00:09:49
* Simple Demo in R and Python - 00:11:00
* Comprehensive explanation of Linear Regression Algorithm - 00:35:47

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