Linear Regression on Iris Dataset

This project demonstrates a simple implementation of linear regression using gradient descent in Python, applied to a subset of the famous Iris dataset.

Overview

We use only the data points where the Iris species is of class 0 (setosa), and perform regression between:

• Feature: Sepal length (cm)
• Target: Sepal width (cm)

Code

• Manual implementation of:
  • Mean Squared Error (MSE)
  • Gradient of cost function
  • Iterative updates to weights (slope) and bias
• Visualization of data points and regression line

Contents

• Linear Regression.ipynb: Jupyter notebook containing all code, plots, and step-by-step execution.

Dependencies

• Numpy
• Pandas
• Matplotlib
• Scikit-learn