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
