Multiple Linear Regression in Python from Scratch Explained Simply

Linear regression in python, in this course we will learn about Linear Regression in Python course. Linear regression is one of the most fundamental techniques in machine learning and statistics. This course provides a comprehensive introduction to linear regression, teaching you how to model the relationship between dependent and independent variables. You will start with the mathematical foundations, then implement linear regression models using Python libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn. You'll explore both simple and multiple linear regression, evaluate model performance using metrics like R-squared and Mean Squared Error, and visualize results. Real-world datasets will be used to apply your skills in practical scenarios, such as predicting house prices or analyzing trends. You’ll also learn about assumptions behind linear regression and how to detect issues like multicollinearity and heteroscedasticity. By the end of the course, you'll be able to confidently apply linear regression in Python to solve real analytical problems. Learn With Jay