Linear Regression Fitting and Plotting

Introduction

In this project, you will learn how to perform linear regression on a set of data points and visualize the results using Matplotlib. Linear regression is a fundamental machine learning technique used to model the relationship between a dependent variable (y) and one or more independent variables (x).

🎯 Tasks

In this project, you will learn:

• How to convert the given data to a Numpy array for easier manipulation
• How to calculate the coefficients of the linear regression model, including the slope (w) and the intercept (b)
• How to plot the data points on a scatter plot and draw the linear regression line on the same plot

🏆 Achievements

After completing this project, you will be able to:

• Prepare data for linear regression analysis
• Use Numpy functions to calculate the linear regression parameters
• Create a scatter plot and overlay the linear regression line using Matplotlib
• Gain a better understanding of linear regression and its practical applications in data analysis and visualization