UETAILab/uetai
Custom ML tracking experiment and debugging tools.
When building machine learning models, it's crucial to understand how your experiments are performing and why. This project helps you track key metrics, visualize your datasets, and debug your models and data, all integrated into popular ML experiment tracking dashboards like Comet ML and Weights & Biases. Machine learning engineers and researchers can use this to gain insights into their model development process.
No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning engineer or researcher who needs better tools to track, visualize, and debug your PyTorch-based machine learning experiments.
Not ideal if you are not working with PyTorch models or if you prefer a standalone debugging solution without integration into an existing ML experiment tracking dashboard.
Stars
15
Forks
1
Language
Python
License
MIT
Category
Last pushed
Aug 02, 2022
Commits (30d)
0
Dependencies
5
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