# 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
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