Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Harish Doddi

Harish Doddi
Cofounder and Chief Executive Officer, Datatron

Website

Harish Doddi is cofunder and CEO of Datatron. Previously, he held roles at Oracle; Twitter, where he worked on open source technologies, including Apache Cassandra and Apache Hadoop, and built Blobstore, Twitter’s photo storage platform; Snap, where he worked on the backend for Snapchat Stories; and Lyft, where he worked on the surge pricing model. Harish holds a master’s degree in computer science from Stanford, where he focused on systems and databases, and an undergraduate degree in computer science from the International Institute of Information Technology in Hyderabad.

Sessions

1:50pm–2:30pm Wednesday, March 7, 2018
Lessons learned deploying machine learning and deep learning models in production at major tech companies
Data science and machine learning
 Location: Expo Hall 1
Secondary topics:  Expo Hall
Harish Doddi (Datatron), Jerry Xu (Datatron Technologies)
Average rating: ****.
(4.00, 3 ratings)
Deploying machine learning models and deep learning models in production is hard. Harish Doddi and Jerry Xu outline the enterprise data science lifecycle, covering how production model deployment flow works, challenges, best practices, and lessons learned. Along the way, they explain why monitoring models in the production should be mandatory. Read more.