Put open source to work
July 16–17, 2018: Training & Tutorials
July 18–19, 2018: Conference
Portland, OR

Technical Lead, Watson Studio, IBM

Atin Sood is a technical lead at IBM’s Watson Studio. For the last 10+ years, Atin has been leading technical teams across IBM focusing on scalable distributed systems and scalable machine learning problems.


11:00am11:40am Wednesday, July 18, 2018
Kubernetes, Sponsored
Location: E147/148
Animesh Singh (IBM), ATIN SOOD (IBM), Tommy Li (IBM)
Animesh Singh, Atin Sood, and Tommy Li demonstrate how to leverage Fabric for Deep Learning to execute distributed deep learning training for models written using multiple frameworks, using GPUs and object storage constructs. They then explain how to take models from IBM's Model Asset Exchange, train them using FfDL, and deploy them on Kubernetes for serving and inferencing. Read more.