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Snowflake ML

Prototype to production machine learning with distributed GPUs or CPUs on the same platform as your governed data. Streamline model development and MLOps with no infrastructure to maintain or configure — all through a centralized UI.

Easy

Integrated end-to-end model pipelines with any open source model on the same platform where your data lives

Efficient

Large-scale training and inference with scalable CPUs or GPUs without infrastructure to configure or maintain

Trusted

Discover, manage, use and govern ML features and models in Snowflake across the ML lifecycle with built-in lineage and monitoring

Screenshot of Snowflake Model dashboard and a streamlit graph

Scalable Model Development

Easily train models with distributed GPUs or CPUs from Snowflake Notebooks on Container Runtime. Use pre-installed, popular libraries such as XGBoost and PyTorch, or pip install any package from open source hubs such as PyPi and HuggingFace.

Continuously Updated ML Features

Create, manage and serve ML features with continuous, automated refresh on batch or streaming data using the Snowflake Feature Store.

Screenshot of Snowflake ML Feature dashboard
Screenshot of Snowflake Model dashboard

Flexible Model Inference

Deploy models for production with distributed GPUs or CPUs from the Snowflake Model Registry, including support for models trained on external platforms. Easily monitor performance and drift metrics with integrated ML Observability.

watch the mlops video

Explore more related features:

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Snowflake provides us with a unified platform that allows us to easily scale up and down without changing the code, providing the speed we need for AI-related projects

Head of Risk Solutions New Product Development
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Bringing familiar modeling capabilities to Snowflake ML has enabled us to more rapidly iterate on our models, improving accuracy and operational efficiency

SVP of Engineering at Decile
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Using Snowflake ML, we've been able to achieve a 70% cost reduction and enhanced agility by moving from running hour-long inference jobs to predictions in near real-time.

CTO, Paytronix
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We can more easily build predictive models and mock up data products all in the Snowflake ecosystem because the data is all there.

Manager of Data Science, IGS Energy
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ON-DEMAND WEBINAR

Technical Deep Dive: How CHG Healthcare Builds Faster Classification Models

End-to-end ML in Snowflake

snowflake ML diagram
LEADING BRANDS LEVERAGE SNOWFLAKE ML

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3Only available in select regions. See documentation for full program details.