How to Optimize Your Models with Intelligent AI Experimentation

Modeling is a scientific process that requires experimentation to get it right. But experimentation is only as effective as the combination of tools and techniques modelers are able to use.

During this session, SigOpt GM Scott Clark discusses an intelligent approach to AI experimentation, including how to design experiments, explore model parameter spaces, and optimize model hyperparameters. This discussion will include guidance on techniques and tools that make this workflow more efficient, effective, and scalable.

You will leave the session with a framework for experimentation, including considerations around metrics, parameters, architectures, runs, and hyperparameter search methods. You will also receive a fully executable notebook that comes with free access to SigOpt so that you can explore what you learn from this session on your own.