The repository consists of an energy forecasting model using XGboost. The dataset consists of hourly energy consumption rates in kWh for an industrial utility.
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Updated
May 1, 2023 - Jupyter Notebook
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energy-forecasting-model
Here are 3 public repositories matching this topic...
Dockerized FastAPI service for forecasting Germany’s hourly electricity load using real Open Power System Data (OPSD). Includes time-series feature engineering, machine-learning baseline model, and production-ready API endpoints.
python docker machine-learning time-series opendata energy-consumption mlops energy-forecasting fastapi energy-forecasting-model mlops-project climate-tech
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Feb 2, 2026 - Python
AI-powered Energy Forecasting System using XGBoost, MLP & LSTM. Includes Flask API, responsive frontend, feature engineering pipeline, notebooks, datasets, and end-to-end machine learning workflow. Perfect for energy analytics, predictive modeling, and ML engineering portfolios.
javascript css python html flask data-science machine-learning ai time-series ml lstm xgboost forecasting mlp energy-consumption smart-energy energy-forecasting energy-forecasting-model energy-analytics iot-energy
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Nov 30, 2025 - Jupyter Notebook
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