A machine learning project aimed at predicting failures in an industrial milling machine using a random forest model.
Email_Spam_Detection is a machine learning project that detects spam emails using a Random Forest model. Features a Flask backend (deployed via Render) and a simple HTML/CSS frontend. Easily deployable for both local and public use.
In this project, we build a predictive model to determine whether a passenger would have survived the Titanic disaster.
This multi-phase project identifies key satisfaction drivers and provides actionable insights to improve customer experience using statistical analysis and machine learning models, including logistic regression, decision trees, random forests, and XGBoost.
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