Ray

Ray

Anyscale
+
+

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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.

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.

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

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

Audience

Companies looking for an open source deep learning training platform that makes building models fast and easy

Audience

ML and AI Engineers, Software Developers

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free
Open source. Consumption-based.
Free Version Supported
Free Trial Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Supported

Company Information

Determined AI
United States
www.determined.ai/

Company Information

Anyscale
Founded: 2019
United States
ray.io

Alternatives

Alternatives

Ray

Ray

Anyscale

Categories

Categories

Deep Learning Supported
Machine Learning Supported

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
Databricks Not Supported
Feast Not Supported
Google Kubernetes Engine (GKE) Not Supported
Hadoop Supported
LanceDB Not Supported
Pachyderm Supported
PyTorch Not Supported
Python Not Supported
Union Cloud Not Supported
io.net Not Supported

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
Databricks Supported
Feast Supported
Google Kubernetes Engine (GKE) Supported
Hadoop Not Supported
LanceDB Supported
Pachyderm Not Supported
PyTorch Supported
Python Supported
Union Cloud Supported
io.net Supported
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