Introduction simple Linear Regression

Welcome to the module on’Linear Regression’.

In this module ,you will start off with a quick introduction to three machine learning techniques: regression, classification and clustering. Then, you will go deeper into one of the most important regression models in machine learning:Linear regression.

You will primarily learn about the following two types of linear regression models:

• Simple linear regression
• Multiple linear regression

In this session

You will get a quick introduction to machine learning models. You will learn about the basics of simple linear regression and understand how to find the best-fitted line for a model and all the various parameters associated with it.

This session covers the following topics:

• Introduction to machine learning
• Supervised and unsupervised learning methods
• The linear regression model
• Residuals
• Residual sum of squares (RSS) and R² (R-squared)

Guidelines for in-module questions

The in-video and in-content questions for this module are not graded. The graded questions are given in a separate segment at the end of the module. These questions will adhere to the following guidelines:

	First Attempt Marks	Second Attempt Marks
Questions with 2 Attempts	10	5
Questions with 1 Attempt	10	0

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