This project demonstrates two types of regression models. Both models are trained and visualized using Python and Jupyter Notebook.
A simple linear regression model predicting profit based on population. The cost function and gradient descent are used to train the model, and the results are visualized.
A multivariate regression model predicting house prices based on size and number of bedrooms. Features are normalized, and gradient descent is used to find the optimal parameters.
