Accelerate ML Insights with Scalable GPUs in Snowflake

As organizations accumulate more data in a wide variety of forms, and as modeling techniques continue to advance, the tasks of a data scientist and ML engineer are becoming increasingly complex. ML developers are turning to Snowflake ML to simplify infrastructure, handle package management challenges, and deploy resource-intensive training workflows with GPUs — all without moving data or limitations on code or libraries they can use.

Join this webinar with ML expert Vinay Sridhar to hear more about ML workflows in Snowflake Notebooks on Container Runtime and learn how to: 

• Easily build advanced ML models such as PyTorch-based recommendation systems or computer vision with distributed GPUs
• Achieve 3-7x faster performance model training using open source libraries outside Snowflake
• Build models using any open source package of choice from HuggingFace