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