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

Animesh Singh
STSM and Program Director, IBM

Animesh Singh is an STSM and lead for IBM Watson and Cloud Platform, where he leads machine learning and deep learning initiatives on IBM Cloud and works with communities and customers to design and implement deep learning, machine learning, and cloud computing frameworks. He has a proven track record of driving design and implementation of private and public cloud solutions from concept to production. In his decade-plus at IBM, Animesh has worked on cutting-edge projects for IBM enterprise customers in the telco, banking, and healthcare Industries, particularly focusing on cloud and virtualization technologies, and led the design and development first IBM public cloud offering.

Sessions

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.