Model that uses 10 different algorithms to predict the revenue of a movie before it's release
IoT-based system to track and manage food waste in grocery stores and restaurants.
A Python implementation of Ridge Regression using scikit-learn to prevent overfitting and handle multicollinearity in regression models. This project applies Ridge Regression on a random generated dataset and visualizes the impact of regularization.
Housing sale price prediction using linear regression, Ridge, KNN, Catboost and XGBoost
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
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