Linear Regression Fitting and Plotting

Beginner

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).

MatplotlibMachine Learning

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

Teacher

labby

Labby

Labby is the LabEx teacher.

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