Webinar: Reproducible Machine Learning: How (Not) to Repeat the Past with W&B
Learn how to set up and leverage reliable and repeatable training and inference pipelines for machine learning projects with W&B.
Created on August 16|Last edited on September 7
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Join us live & ask questions!
🙋♀️Interactive live presentation + Q&A with Deep Learning Engineer, Stacey Svetlichnaya
What you'll learn?
Reliably reproducing deep learning research—whether from others' code or your own past attempts—is a notorious challenge in machine learning.
With W&B logging and artifacts for dataset and model versioning, you can effortlessly
- track all the details of your ML workflows,
- revisit earlier states of your whole organization's development cycle (whether in code, data, config, or model checkpoints), and
- train models more confidently, knowing you won't lose progress or need to retrace important steps.
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