Webinar: Building Reproducible Pipelines

We're excited to announce our special guests for this upcoming W&B Webinar!. Made by Andrea Pessl using Weights & Biases
Andrea Pessl
One of the most important and underrated components of modern machine learning research is quick prototyping and experimentation while preserving reproducibility.
Having a pipeline that facilitates and abstracts away many of the low level building blocks is absolutely essential for success; especially true in a fast-paced, multidisciplinary team.
We're excited to announce a pair of special guest speakers at our next webinar. Join Sairam Sundaresan & J. Emmanuel Johnson, 2 participants of the FDL Heliophysics research challenge who'll discuss how important it is to have a robust ML pipeline that facilitates later success - especially in a fast-paced multidisciplinary team.

Register here for the live webinar!

What to expect?

Read more on the background of our guests:

J. Emmanuel Johnson is is a PhD candidate at the University of Valencia, Spain. He is an applied Machine Learning researcher with a particular interest in scalable probabilistic and generative models.
Sairam Sundaresan is a Deep Learning Research Engineer at Intel Labs, California. His work includes algorithms and methods for object tracking, real time 3D reconstruction, gesture recognition, low-level computer vision functionalities, mixed-precision deep network training and efficient deep learning algorithms for custom accelerators.