Building Robust ML Production Systems Using OSS Tools for Continuous Delivery for ML

Explore a comprehensive conference talk on implementing Continuous Delivery for Machine Learning (CD4ML) using open-source tools to build robust ML production systems. Learn how to extend DevOps practices to ML workflows, addressing challenges such as manual testing, infrequent deliveries, and lack of versioning for data and hyperparameters. Discover how Merantix Momentum applies MLOps culture and leverages vendor-agnostic tools like Flyte, MLflow, Squirrel, Hydra, and Seldon to create ML systems that continuously train, test, deploy, and monitor models across various industries. Gain insights into automating and testing processes from data validation to model deployment, versioning data, code, and hyperparameters, and implementing statistical metric monitoring to trigger retraining when models decay.