JUNE 24 | 11 AM PT | 2 PM ET
Join Provectus and AWS as we discuss how Kubeflow and Amazon SageMaker complement one another to enable MLOps and reproducible ML, and explain how to design and build ML infrastructure on AWS for agile enterprises.
We will take you through major components of a secure and compliant infrastructure for Machine Learning:
- Reusable Feature Store with reproducible data preparation pipelines
- Reproducible experimentation & model training pipelines
- Continuous Integration and Delivery for ML (MLOps)
- Production monitoring and model re-training
The webinar is ideal for data science teams looking to deploy their work faster, and for DevOps and IT engineers struggling with ML operational tasks. It is illustrated with real-world case studies.