README.md

metadata

title: Engine Condition Prediction
sdk: docker

Engine Condition Prediction

This Streamlit application predicts the engine condition (Normal or Faulty) using an XGBoost machine learning model.

Model Details

• Algorithm: XGBoost Classifier
• Model Source: Hugging Face Model Hub
• Input Features:
  • Engine rpm
  • Lub oil pressure
  • Fuel pressure
  • Coolant pressure
  • lub oil temp
  • Coolant temp

How It Works

1. User enters real-time engine sensor values.
2. The app loads a pre-trained XGBoost model from Hugging Face.
3. The model predicts the engine condition.
4. Inputs and predictions are stored in a CSV file for logging.

Deployment

• Framework: Streamlit
• Containerized with: Docker
• Hosted on: Hugging Face Spaces

Dependencies

All dependencies are defined in requirements.txt and installed during Docker build.

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