SAS Tutorial | How to Pick Hyperparameters of Machine Learning Models

How many neurons should you use in your neural network? If you’re unsure exactly how to improve machine learning model performance, or you’re spending too much time model tuning, let SAS’ Aurora Peddycord-Liu guide you through the BAAM (Baseline Autotune Adjust Monitor) approach to pick hyperparameters. In this SAS How To Tutorial, she tells you the differences between parameters and hyperparameters and demonstrates hyperparameter autotuning in Model Studio.

Download the data

Chapters
00:00 – Intro
00:55 – Learn the differences between parameters and hyperparameters
01:43 – Pick hyperparameters with the BAAM (Baseline Autotune Adjust Monitor) approach
01:53 – Demo of Baseline in SAS Model Studio
05:00 – Autotune demo
09:09 – Learn about the Adjust step that weighs two factors: Complexity and Generalizability
11:31 – Monitor model performance and update periodically demo
12:53 – Summary of BAAM

Learn more about SAS Software

Other Machine Learning Tutorials

SUBSCRIBE TO THE SAS USERS YOUTUBE CHANNEL #SASUsers #LearnSAS

ABOUT SAS
SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.

CONNECT WITH SAS