There are three core components to SigOpt:
- Runs: Execute a run to track training and organize modeling attributes
- Dashboard: Create projects, customize visualizations, and collaborate with teams
- Experiments: Automate hyperparameter optimization
Complementing these core components are a wide variety of features designed to further boost your modeling workflow. Foremost among these relates to features designed to help you get the most out of metrics and connect them back to business value.
Metrics can be tough to define, analyze, understand, and select. So SigOpt developed Metric Strategy to empower our users to store up to 50 metrics, apply up to 4 metrics as constraints, and optimize 2 metrics at the same time. We know that rigorous machine learning requires balancing a variety of metrics at once, so we wanted to give you the tools to do so.
As you execute Runs, SigOpt will store your metrics so you can visualize any of them in our Dashboard. And as you apply metrics as constraints or optimize across multiple metrics for any hyperparameter tuning job, our intelligent algorithms take this information into account to efficiently give you novel insights on your parameter space. Here is an example of a Pareto frontier from a multimetric experiment in SigOpt’s Dashboard:
We hope you take advantage of this feature in SigOpt to manage your metrics. Read this blog post to learn more about how to utilize these features on your projects: Introducing Metric Management.
If you want to try out the product, sign up for free access, execute a run to track your training, and launch an experiment to automate hyperparameter optimization. If you want to learn more about our products, track industry news, and hear from our research team, follow our blog or subscribe to our youtube channel.
