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Tetouan City Machine Learning Project to Predict Power Consumption Changelog

Produced a predictive model for power consumption in Tetouan City using Machine Learning in Python, leveraging weather and time-related variables such as diffuse flow from UCIML Repo.

2024-04-15

Collected and preprocessed Tetouan City power consumption dataset from UCIML

2024-05-01

Performed exploratory data analysis; identified key weather and time variables

2024-05-20

Implemented and compared multiple regression models (Linear, Random Forest, AdaBoost)

2024-06-10

Optimized AdaBoost model hyperparameters; achieved 94.5% prediction accuracy

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