Introducing Metric Management
A solution that helps you craft the right combination of bounds, thresholds, and strategy to ensure your model perfectly fits your business needs
SigOpt provides a “human-in-the-loop” process so that you can guide the platform’s discovery of a more effective set of parameters for your model, based on external business factors or domain-specific expertise. This process is called Metric Management, and is enabled by a variety of tools built into our API and web interface.
In this webinar, we will introduce Metric Management, which includes the following advanced features:
We will give an overview and a live demo of each feature, and show how they are more valuable when used in concert rather than independently. Sign up for the webinar to learn more!
Barrett crafts product messaging for both technical practitioners and senior decision makers. He is a graduate of Yale University where he studied economics and international studies. He also studied electrical engineering at Columbia, prototyped augmented reality glasses at Meta, marketed robotics developer kits at NVIDIA, and wrote launch and evergreen content for machine learning products at Google Cloud.
Harvey is a research engineer at SigOpt with a strong interest in stochastic optimization and machine learning. At SigOpt, he applies these interests to develop novel implementations of optimization algorithms for enterprise and academic users. Prior to SigOpt, Harvey obtained his Ph.D. in electrical engineering from Princeton University, where his doctoral studies focused on approximate dynamic programming, stochastic optimization, and optimal learning with applications in managing grid-level battery storage. He also holds a B.S. in electrical engineering from the University of Texas at Austin.