How to track model changes in Django and execute dependent workflows
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Updated
Aug 18, 2023 - Python
How to track model changes in Django and execute dependent workflows
Automate the tracking, downloading, and analysis of AI papers from HuggingFace. Stay updated with cutting-edge research effortlessly! 🐙📄
Covers essential features like model tracking, versioning, and experiment, providing a foundation for efficient ML project lifecycle management.
MLflow adapter for CrateDB.
Credit Scoring model using XGBoost, tracked with MLflow, and explained using SHAP for interpretability.
An end-to-end MLOps pipeline for automating the training, deployment, and monitoring of a machine learning application designed to assess mental well-being signals based on behavioral data.
Add a description, image, and links to the model-tracking topic page so that developers can more easily learn about it.
To associate your repository with the model-tracking topic, visit your repo's landing page and select "manage topics."