The fastest and easiest way to build deep learning models.
Ship DL Features Faster

Train Models
Faster

Build More Accurate Models

Build More
Accurate Models

Share GPU Clusters

Get More Out of
Your GPUs

Scale Your Deep Learning Team

Track and Reproduce
Your Experiments

Deep Learning in hours and minutes, not days and weeks.

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Ship models faster and do more science!

Our open-source deep learning platform enables you to train models in hours and minutes, not days and weeks.

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Focus on research and models

Instead of arduous tasks like manual hyperparameter tuning, re-running faulty jobs, and worrying about hardware resources.

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Distributed training as it was meant to be

Our distributed training implementation outperforms the industry standard, requires no code changes, and is fully integrated with our state of the art training platform.

Share resources, experiments, and data
— and do it safely.

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Real-time experiment dashboard

With built-in experiment tracking and visualization, Determined records metrics automatically, makes your ML projects reproducible, and allows your team to collaborate more easily.

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Sophisticated checkpointing and resource scheduling

Your researchers will be able to build on the progress of their team and innovate in their domain, instead of fretting over errors and infrastructure.

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Expert built for expert teams

We’re dedicated to the science of Deep Learning and are leaders in productionizing DL workflows, and we can’t wait to help your team thrive.

Your team, your infrastructure, your tools
— we support it all.

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Serious compatibility

Determined works with the leading deep learning frameworks— PyTorch, TensorFlow, and Keras. We support a variety of data storage systems, and make it easy to export models to downstream serving systems.

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Your infrastructure, your choice

Our platform integrates with your hardware, whether you’re in the cloud or on-premises.

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Get the most out of your hardware

Determined enables all of your training-related workloads to run seamlessly on the same machines.

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