Some things are best learned through real-world experience. Machine learning is no different. Getting machine learning right requires evolving your analytics platform to support moving data science from research into operations. It all begins with repeatable data wrangling processes that support building and deploying models. It also requires collaboration between data scientists, engineers and business analysts. With the help of tools like SAS® Model Manager, these teams can continuously and automatically train models at scale and ensure the best models are put into production.
In this latest Data Science Central webinar we will discuss:
Model validation best practices
Various model deployment options including open source models
Model scoring and training services
Model performance monitoring
Orchestrating a continuous learning platform
Speakers:
Wayne Thompson, Chief Data Scientist – SAS
Lora Edwards, Principal Product Manager – SAS
Hosted by:
Rafael Knuth, Contributing Editor – Data Science Central
