ML Monitoring Fundamentals
How to supervise all of your production models, debug quickly, and have peace of mind
Tired of wild goose chases? Or the terror of no monitoring at all? There’s got to be a better way to supervise and debug machine learning models in production. (Hint: there is.)
Effective ML model monitoring is a key part of AI Quality management. Monitoring ensures that your machine learning models are high performing and delivering value. The problem? Most model monitoring solutions today are inaccurate and ineffective, leading to too much wasted time and effort. Data scientists and MLOps teams deserve better.
Join us on March 30th as TruEra’s President and Chief Scientist, Anupam Datta, provides an overview of the fundamentals of ML Monitoring.
During the 40-minute webinar, we will cover:
- Why ML model monitoring is critical to business success
- The problems with ML monitoring today - alert fatigue, wild goose chases, cobbled-together ad hoc approaches
- Monitoring best practices - what you should be looking out for
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Meet the Speaker
President and Chief Scientist
TruEra provides AI Quality solutions that analyze machine learning, drive model quality improvements, and build trust. Powered by enterprise-class Artificial Intelligence (AI) Explainability technology based on six years of research at Carnegie Mellon University, TruEra’s suite of solutions provides much-needed model transparency and analytics that drive high model quality and overall acceptance, address unfair bias, and ensure governance and compliance.