I built the Energy-Recommender-Using-AI full‑stack AI application that analyzes household energy consumption patterns and gives personalized recommendations for efficiency, safety, and cost savings. The repo lives on my GitHub under the handle @Nazakath‑Kanz.
Purpose: AI‑powered analysis of household energy usage with recommendations for efficiency, safety, and cost savings.
Tech Stack – Backend: Python, FastAPI, Uvicorn, scikit-learn Frontend: React, Tailwind CSS Data: UCI Household Power Consumption dataset (2M+ records), synthetic edge‑case profiles.
External data storage – due to GitHub's file size limits, the datasets and trained model are hosted externally on Google Drive.
Project start date = 2026‑06
Last update = 2026‑07
cd backend
python -m venv venv
venv\Scripts\activate # Windows
pip install -r requirements.txt
python -m uvicorn app.api:app --reload --host <redacted> --port 8000
# Wait for "Application startup complete"
cd ../frontend
npm install
npm start
Backend readiness log line = Application startup complete