Recorded Webinar

How to Productionize ML Models at Scale

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.

Key discussion topics:

  • Implications of large scale models in operations
  • Challenges in taking models to production
  • Best practices of ML to production
  • Data Engineering Maturity
  • Operationalizing in the cloud
  • Sigmoid’s cutting edge approach

Watch Recorded Webinar

Scott Kasper

Director Data Engineering Yum Brands

Rahul Singh

Chief Analytics Officer and Co-Founder Sigmoid @Sigmoid

Mayur Rustagi

CTO & Cofounder Sigmoid @Sigmoid

Tenzin Namdak

Director of Big Data and advanced analytics Sigmoid @Sigmoid