RayAnyscale
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Related Products
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About
Distributed training without changing your model code, determined takes care of provisioning machines, networking, data loading, and fault tolerance. Our open source deep learning platform enables you to train models in hours and minutes, not days and weeks. Instead of arduous tasks like manual hyperparameter tuning, re-running faulty jobs, and worrying about hardware resources. Our distributed training implementation outperforms the industry standard, requires no code changes, and is fully integrated with our state-of-the-art training platform. With built-in experiment tracking and visualization, Determined records metrics automatically, makes your ML projects reproducible and allows your team to collaborate more easily. 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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About
Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Companies looking for an open source deep learning training platform that makes building models fast and easy
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Audience
ML and AI Engineers, Software Developers
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Pricing
Free
Open source. Consumption-based.
Free Version
Supported
Free Trial
Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
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Company InformationDetermined AI
United States
www.determined.ai/
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Company InformationAnyscale
Founded: 2019
United States
ray.io
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
Amazon SageMaker
Supported
Amazon Web Services (AWS)
Supported
Apache Airflow
Supported
Google Cloud Platform
Supported
MLflow
Supported
TensorFlow
Supported
Amazon EC2 Trn2 Instances
Not Supported
Amazon S3
Supported
Apache Spark
Supported
Dask
Not Supported
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Integrations
Amazon SageMaker
Supported
Amazon Web Services (AWS)
Supported
Apache Airflow
Supported
Google Cloud Platform
Supported
MLflow
Supported
TensorFlow
Supported
Amazon EC2 Trn2 Instances
Supported
Amazon S3
Not Supported
Apache Spark
Not Supported
Dask
Supported
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