Building Automated Model Life Cycles to Show Data Science Business Contribution and Minimize Impact

Explore the intricacies of designing and implementing automated model life cycles in this insightful 49-minute conference talk by Jim Olsen, Chief Technology Officer at ModelOp. Delivered at the Toronto Machine Learning Series (TMLS), the presentation delves into industry best practices for creating effective model life cycles, emphasizing their role in demonstrating the business value of data science initiatives. Learn about key considerations in the development process, identify essential stakeholders to involve, and understand critical issues that must be addressed. Gain valuable knowledge on how to optimize your model life cycle to maximize business impact while minimizing potential drawbacks.

Building Automated Model Life Cycles to Show Data Science Business Contribution, Minimize the Impact