A Better Approach to Metrics, Training, and Tuning with MLconf

Nick Payton
Advanced Optimization Techniques, Applied AI Insights, Deep Learning, Experiment Management, Hyperparameter Optimization, Machine Learning

SigOpt collaborated with MLconf on a webinar to discuss best practices for metrics, training, and hyperparameter optimization for developing high-performing models. During this talk, SigOpt Head of Product Fay Kallel and Head of Engineering Jim Blomo shared insights that they’ve developed from working with a wide range of modelers on the SigOpt platform. 

Watch this video to follow an applied fraud detection use case to learn how to:

  • Discover, track, and compare many metrics to understand model behavior and connect machine learning to business outcomes
  • Track, visualize, and analyze training runs to create baselines, interpret model convergence, and explore the modeling problem space
  • Automate, accelerate, and scale hyperparameter optimization to identify configurations of your model that meet specific business needs


If you want to try out the product,
join our beta program for free access, execute a run to track your training, and launch an experiment to automate hyperparameter optimization.

Nick Payton
Nick Payton Head of Marketing & Partnerships