webhook

Automated Machine Learning Model Deployment Pipeline

Orchestrates data preprocessing, model training, and deployment with integrated error handling for data quality checks, AI-driven model selection, version control, and real-time performance monitoring.

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Kurulum Kılavuzu

1. Configure the Webhook trigger with your data source. 2. Set up the Data Preprocessing Code node with your transformation logic. 3. Define data quality rules in the Data Quality Check Code node. 4. Provide the training API endpoint in the Model Training HTTP Request node. 5. Configure the Model Selection HTTP Request to call your model registry. 6. Set Git repository details in the Version Control node. 7. Provide deployment API endpoint in the Deployment HTTP Request. 8. Configure the Performance Monitoring HTTP Request to send metrics. 9. Set up error notification (e.g., email) in the Error Handling node.