Unlocking MLOps capabilities with Snowflake

Join our webinar to explore the powerful MLOps capabilities within Snowflake’s Data Cloud.

Discover how Snowflake streamlines the end-to-end machine learning lifecycle starting from data preparation and model training to deployment, including monitoring and observability for production workloads.

During the webinar we are going to take a look at advancement in MLOps in Snowflake that make everyday life of Data Scientists, ML Analysts and Analytics Team Leaders much easier and as a consequence lead to gaining competitive advantage of your organisations in terms of AI adoption.

Learn how Snowflake’s MLOps capabilities enable teams to:

• Simplify Data Access and Preparation: Leverage Snowflake’s secure, governed, and scalable data platform to access clean, curated data for training and inference — with no data movement required.

• Build and Train Models with Flexibility: Integrate seamlessly with leading ML frameworks and tools such as Python, scikit-learn, MLFlow, and more, using Snowpark and external functions.

• Deploy Models with Confidence: Discover how to register, version, and deploy models directly within Snowflake, ensuring reproducibility and governance at scale.

• Monitor and Manage ML Pipelines: Learn about best practices for tracking performance, monitoring drift, and automating model retraining using native features of Snowflake MLOps.

• Collaborate Across Teams: Enable data scientists, data engineers and business users to work together more efficiently by centralizing data and ML workflows in a single platform.