4th year ODD semester Industrial Attachment related notebooks.
Notebook used to test Linear Regression model and RandomForest Classifier on to see which one can accurately predict the price range between cellphones.
A notebook aimed at predicting and improving water safety by analyzing contaminants and pollution levels in water sources, enhancing public health and ensuring access to clean drinking water.
Predict tomorrow's S&P 500 index price using historical data. The data analysis has been preformed mainly using Jupyter Notebook and Python Machine Learning library of sklearn -RandomForestClassifier
Classification Machine Learning project
DVD Rental Prediction leverages regression models to forecast rental duration, guiding optimal inventory management for DVD rental companies. It combines data visualization, feature engineering, and model evaluation within a Jupyter Notebook to deliver actionable insights.
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