ML Pipeline Starter
Build production ML pipelines.
Features
Data Processing
- Data validation
- Feature engineering
- Data augmentation
Model Training
- Hyperparameter tuning
- Cross-validation
- Model versioning
Evaluation
- Metrics tracking
- Bias detection
- Performance monitoring
Deployment
- Model serving
- A/B testing
- Rollback support
Quick Start
# Create pipeline
./ml-pipeline.sh create my-model
# Train
./ml-pipeline.sh train my-model
# Deploy
./ml-pipeline.sh deploy my-model production
Frameworks
- TensorFlow
- PyTorch
- Scikit-learn
Requirements
- Python 3.8+
- Docker
Author
Sunshine-del-ux