Description

Data is the new oil and companies across various industries are moving towards data driven decision making. This session covers the landscape from a CPG perspective to showcase the power of MLOps in managing ML practice in a Fortune 500 company.

We draw parallels to our experience (use case: Running effective Trade Promotions) with one of our clients to contextualize the challenges faced by Data Science & Business Leaders in their day-to-day. Also, in a world where ML Platforms focus on enabling Data Scientists to build more and learn more, business leaders are somewhere losing the race. This gap can be bridged with a verticalized MLOps platform - what goes into building one and what is the need which is hiding in plain sight?

Instructor's Bio

Pavan Nanjundaiah

Head of Product Engineering at Tredence Inc.

Pavan Nanjundaiah - Leading a machine learning based analytical product platform that specializes in ML Model Management (MLOps) and Data Quality Management. Responsibilities include designing the core product platform and managing a team of Data Scientists, Data Engineers and Architects. Experienced in delivering large Data Engineering/Data Science projects for Fortune 500 clients using cloud platforms like Microsoft Azure, AWS and Big Data technologies.


Vamsi Krishna Bhupasamudram - CPG & Retail Consulting at Tredence Inc.

Vamsi Krishna Bhupasamudram - AI Consulting leader with 12+ years of rich experience of partnering with Fortune Global 500 companies across Food & Beverages, CPG and Retail. Functional Expertise: Marketing Strategy & Execution, Merchandising, Customer Experience, Hyper Personalization.


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Webinar

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    How to Manage ML at scale in CPG

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