Linear Regression with Gradient Descent

This project demonstrates linear regression using the gradient descent method. Two scenarios are explored:

1. Profit Prediction based on the number of customers per day.
2. House Price Prediction based on house size and the number of rooms.

Scenario 1: Profit Prediction

• Libraries Used: numpy, pandas, matplotlib
• Data: The dataset consists of two columns: Profit (target) and Customer Number per Day (feature).

Scenario 2: House Price Prediction

• Libraries Used: numpy, pandas, matplotlib
• Data: The dataset consists of three columns: Price (target), House Size, and Room Number (features).

How to Use

1. Download the .py file from this repository.
2. Run the file in your Python environment or copy the code into your own script.

Metrics and Visuals

Metrics such as cost function values and Mean Squared Error (MSE) are illustrated by graphs included in the visuals, which are plotted during the execution of the script.