Your AI data scientist for automated machine learning, monitoring, and debugging.

• AutoML Capabilities

  • Automated feature engineering and selection
  • Model selection and hyperparameter optimization
  • Cross-validation and performance evaluation
  • Automated report generation

• 24/7 Model Monitoring

  • Real-time performance tracking
  • Drift detection and alerts
  • Automated model retraining triggers
  • Custom monitoring dashboards

• Intelligent Debugging

  • Automated error detection and diagnosis
  • Performance bottleneck identification
  • Data quality checks and validation
  • Model behavior analysis

• Python 3.10+

RapidML can be customized through a configuration file:

automl:
  max_time: 3600
  optimization_metric: "f1"
  cross_validation: 5

1. Automated Model Development

   • Quick prototyping of ML solutions
   • Automated feature engineering
   • Model selection and optimization

2. Production Monitoring

   • Continuous model performance tracking
   • Automated alerts and notifications
   • Drift detection and handling

3. Debugging and Optimization

   • Performance troubleshooting
   • Model behavior analysis
   • Automated error resolution

We welcome contributions! Please see our Contributing Guidelines for details.

This project is licensed under the MIT License - see the LICENSE file for details.

• Advanced AutoML features
• Integration with major cloud platforms
• Enhanced monitoring capabilities
• Extended debugging tools

• GitHub Issues: Create an issue

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