AIMI Trainee Meeting: Reproducible Machine Learning at Scale Using PyTorch and W&B - Lavanya Shukla
Reproducible machine learning at scale using PyTorch and W&B
How can we support effective, reproducible, and explainable deep learning and coordination across practitioners? In this talk, Lavanya Shukla will share best practices for conducting, debugging, and sharing deep learning experiments at scale. She will talk through how some of the best tech companies in the world use the Weights & Biases platform for managing datasets, debugging models, versioning training/evaluation recipes, extracting insights, and storing all the crucial details needed to make their models reproducible and their research collaborative.
Lavanya is the Head of Growth at Weights and Biases, an experiment tracking platform for deep learning. She began working on AI 10 years ago when she founded ACM SIGAI at Purdue University as a sophomore. In a past life, she taught herself to code at age 10, and founded the machine learning startup Dataland. You can find her on twitter @lavanyaai