model-registry-201

Name		Name	Last commit message	Last commit date
parent directory ..
Consuming_Registered_Models.ipynb		Consuming_Registered_Models.ipynb
Logging_Models_HuggingFace.ipynb		Logging_Models_HuggingFace.ipynb
Logging_Models_PyTorch.ipynb		Logging_Models_PyTorch.ipynb
Logging_Models_PyTorch_Lightning.ipynb		Logging_Models_PyTorch_Lightning.ipynb
Logging_Models_by_Reference.ipynb		Logging_Models_by_Reference.ipynb
README.md		README.md

README.md

This repository contains materials for our Weights & Biases 201: Model Registry course.

Master the process of logging and managing models in a centralized model registry, allowing for an organized and efficient model management workflow.

Gain hands-on experience in accessing, evaluating, and automating downstream processes of models, aiding in robust model deployment and monitoring.

Learn to build dynamic, auto-updating reports showcasing model evaluation and automation processes, enabling clear communication with stakeholders.

Notebooks can be run on your local system or via Google Colab
If you have questions, you can ask them in Discord in the #courses channel

🚀 Enroll for free