How to Productionize ML Models at Scale
July 16th, 2020
11 AM PST (2PM EST)
Artificial intelligence (AI) and machine learning (ML) are quickly becoming the de-facto tool to affect the bottom line of the organization. Despite the industry being in exponential growth in recent years, 85% of trained machine learning models are never deployed in the real world. (Source: NewVantage Partners)
The widest gap is between data scientists and IT. Organizations often cite a wide variety of complexities when they want to use AI / ML models in operation with production scale data in the real world – from data management, integration, security and real-time analytics.
Topics covered:
Speakers
Scott Kasper
Director Data Engineering- Yum Brands
Mayur Rustagi
CTO & Cofounder Sigmoid
Mayur has an experience of 11+ years in designing end to end architectures and building data pipelines for big data applications. He has led the development of hundreds of such data pipelines in production systems for leading organizations and has put complex ML models into production
Rahul Singh
Chief Analytics Officer & Cofounder Sigmoid
Rahul has more than 11 years of experience in building intelligent self-learning systems. Rahul and his team bring in a core problem-solving mindset to help businesses with their AI architectures and ML models which transform into continuous actionable insights
Moderator
Tenzin Namdak
Director of Big Data and advanced analytics Sigmoid
With over 10 years of experience in crafting technology solutions, Tenzin works with enterprises that are on a transformation journey to streamline their technology infrastructure across domains, through a data first approach