This repository contains various regression models built using Python, including Linear Regression, Polynomial Regression, and Multiple Linear Regression. Each model is trained and evaluated on real-world datasets with clear visualizations using Matplotlib and Seaborn.

This project demonstrates the use of machine learning models to estimate a pore pressure proxy using geological well log data. Based on the Well Log Facies Dataset, the project simulates pore pressure from petrophysical features like GR, ILD_log10, PE, DeltaPHI, PHIND, NM_M, and RELPOS. Multiple regression models—including Linear Regression, Ridge