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Building enduring business value using ML Ops

Webinar: Monday, 14 November 2022 - Fireside Chat Tech Series

14.11.2022 / Bangalore, Online
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FIRESIDE CHAT TECH SERIES

A webinar on ‘Building enduring business value using ML Ops’

Building ML models is not just about Training, Testing, and Deploying. The challenge lies in maintaining the ML Models in production without degrading performance. One has to face many unique situations in building enterprise-level ML models. However, one can apply DevOps principles similar to those used to operationalize applications for operationalizing ML Models as well. This approach helps solve many challenges in production alongside strongly coupled pipelines that can perform seamlessly and give any organization better business value in the long run.

In this Fireside chat, we have the pleasure of hosting a Technology and Operations expert Vishal Bhasin, SVP at Data Axle. Vishal, in a career of over two decades as a transformational technology leader has had extraordinary success in positively impacting revenue and increasing performance by setting up and scaling world-class teams in enterprises. He has established and led digital transformation practices and culture focusing on operational efficiency and customer experience.

In this session, we will understand the fundamentals of ML Ops, where different industries and organizations are in their journey, and what they need to imagine, define and do to achieve maturity. We will also focus on the ground-level barriers for businesses to take this journey to realize business value.

 

Date: Monday, November 14, 2022

Time: 7:00 pm - 8:00 pm IST I 8:30 am – 9:30 am EST I 7:30 am – 8:30 am CST |

Speaker: Vishal Bhasin, SVP, Technology and Operations, Data Axle

Host: Abhishek Pandey, Senior Consultant, Digital Innovation, Tietoevry Create India

 

We look forward to your participation in this Fireside chat series.

 

Contact us

Abhishek Pandey

Senior Consultant, Digital Innovation, Tietoevry Create India

Date and place

14-11-2022
05:00-06:00 UTC

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