Sales Time Series Forecasting using Machine Learning Techniques (Random Forest, XGBoost, and Stacked Ensemble Regressor)
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Updated
Jun 28, 2023 - Jupyter Notebook
Sales Time Series Forecasting using Machine Learning Techniques (Random Forest, XGBoost, and Stacked Ensemble Regressor)
My solutions for the 2023 Cloudflight Coding Contest (AI Category)
The current project introduces a script building a stacked learning ensemble, containing a single multilayered ANN (meta-learner) trained using the predictions of a number of ANNs (Level-0 learners).
🇵🇱🏠 The project predicts an apartment price for Warsaw, Krakow and Poznan. Distributed apartments by districts using geopandas; built XGBoost model with MAPE = 9% (the best of others).
Predict Skin Irritation based on pIC50 using command-line tool application
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