End-To-End ML With GPUs In A Snowflake Notebook With Container Runtime

Developing and deploying ML models to production can be challenging while dealing with package dependencies, configuring resources for scalability, and ensuring environment isolation. This session, recorded for BUILD 2024, showcases how easy and seamless it is to build and productionize ML workflows with any Python package directly from Snowflake Notebooks on the Container Runtime. This makes resource-intensive ML use cases, such as deep learning, simpler and more accessible than ever before.

Learn how easy it is to productionize a PyTorch computer vision model with GPUs for development and inference in Snowflake ML.

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