The MLOps Live Webinar Series is a complimentary webcast focusing on managing and automating machine learning pipelines to bring data science into real business applications. The technical track delivers on the “how-to”, with data scientists offering dedicated training, hands-on direction and live demos on operationalizing machine learning at scale and in real time.
In this session you will learn:
- Why and how models lose their accuracy due to concept drift and the problems this poses for data scientists and ML engineers
- What methodologies exist for concept drift detection and the different options available for handling concept drift once it has been detected
- How to implement concept drift detection and remediation in production, and:
- Automatically detect concept drift by monitoring and understanding whether your models have been impacted
- Harness automated tools for adjusting models
- Utilize online models that adapt to shifting data
- Monitor concept drift in an ongoing manner by setting up alerts and tracking error rates
- How to automate MLOps processes at scale to handle drift detection using open source tools – a live demo will be shown
Presented By
Yaron Haviv,
Co-Founder and CTO, Iguazio
Or Zilberman,
Data Scientist, Iguazio