Optimizing and Evaluating Hyperparameter Models for Better Performance (Tutorials 5-6)

Tutorials 5 and 6 in the AMPL series focus on hyperparameter optimization and model evaluation, giving users the tools to enhance their models for more accurate predictions in cheminformatics and drug discovery.

Tutorial 5 teaches how to build and interpret parameter dictionaries, perform hyperparameter searches, and analyze different model candidates to identify the best-performing configurations. This helps users fine-tune their models for optimal results.
Tutorial 6 takes it further by helping users visualize performance trends and compare key model metrics, like precision and recall, to assess how well the model generalizes to new data.
These tutorials equip users with the knowledge to create robust, optimized models and gain deeper insights into how hyperparameters influence performance, improving the accuracy and reliability of predictions.

Видео Optimizing and Evaluating Hyperparameter Models for Better Performance (Tutorials 5-6) канала ATOMScience-org