🔋 AI-Powered Energy Forecaster

Machine Learning Pipeline for Building Energy Prediction — Designed for Insight, Built for Deployment

AI-Powered Energy Forecaster 🔋⚡

A production-grade machine learning pipeline designed to forecast building heating loads using architectural and environmental data. Built with performance, clarity, and explainability in mind, this project combines FastAPI, scikit-learn, and SHAP for real-time inference and transparent model interpretation.

Ideal for roles in AI engineering, machine learning development, or data-driven energy analysis, this repo highlights:

• Deployment-ready model serving with FastAPI
• Batch prediction automation via client scripts
• End-to-end explainability with SHAP visualizations
• Clean modular code for scaling and refinement

Whether you're evaluating predictive modeling skills, backend API integration, or AI explainability, this project reflects a strong foundation in applied machine learning practices.

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🚀 Features

• Trains and evaluates a regression model on real-world energy data
• Serves predictions via a FastAPI endpoint at /predict
• Batch testing with predict_client.py for real-time inference
• SHAP integration to visualize feature contributions per prediction
• Heatmaps and pairplots for model + data storytelling
• Notebook included: ai_powered_energy_forecaster.ipynb

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🏷️ Tags

#machine-learning #fastapi #energy-modeling #regression #shap #explainable-ai #python #ai-engineering #api #sustainability

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📂 Repo Structure

├── api/                    # FastAPI app to serve the model
├── models/                 # Training scripts and saved .pkl model
├── inference/              # Lightweight prediction interface
├── outputs/                # Batch predictions and SHAP visuals
├── ai_powered_energy_forecaster.ipynb  # EDA + SHAP notebook
├── predict_client.py       # POSTs sample payloads to API
├── requirements.txt
└── README.md

📄 License
This project is licensed under the MIT License — feel free to use, modify, and share it as long as you include proper attribution.

👤 Author
Created by Dartayous — blending cinematic storytelling and AI engineering to deliver intelligent, creative tech.

🔗 GitHub Profile

🧠 [LinkedIn or personal portfolio link if you want to include it later]