DAY 1Track 1
ModelOps: Improving Success Rate & Speed-to-Market of AI initiatives
More and more, organizations are relying on machine learning (ML) models to turn massive volumes of data into fresh insights and information. When 50% of models never make it into production, what can you do to improve the odds?
ModelOps is how analytical models are cycled from the data science team to the IT production team in a regular cadence of deployment and updates. In the race to realize value from AI models, it’s a winning ingredient that only a few companies are using.
Jason Loh Head of Analytics, SAS Asia Pacific
Jason Loh is the Asia Pacific General Manager of SAS Global Technology Practice – Analytics. He has extensive experience in advanced analytics. He specializes in artificial intelligence, machine learning, natural language processing (NLP) technology and data mining and analytical lifecycle management, and has experience in collaborating with companies in various industries in this field.
For the past 10 years, SAS has supported analytical projects from a variety of clients, including finance, manufacturing, public and telecommunications, in 13 countries in Asia, and serves as a leading media conference, conference and expert panel in each country.
Jason Loh holds a double major in IT and Marketing from Monash University, Australia.
-AI / machine learning technology trend
-Current Status and Case Studies of Artificial Intelligence Applications in Global Companies
-Machine learning life cycle management
-Natural language processing techniques and business application strategies