Model that uses 10 different algorithms to predict the revenue of a movie before it's release
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Updated
Dec 2, 2020 - Jupyter Notebook
Model that uses 10 different algorithms to predict the revenue of a movie before it's release
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
IoT-based system to track and manage food waste in grocery stores and restaurants.
Housing sale price prediction using linear regression, Ridge, KNN, Catboost and XGBoost
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.
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