RayAnyscale
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Related Products
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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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About
Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates.
Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script.
W&B Weave is here to help developers build and iterate on their AI applications with confidence.
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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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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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Audience
ML and AI Engineers, Software Developers
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Audience
Developers interested in a powerful MLOps and LLMOps suite
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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
Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Open source. Consumption-based.
Free Version
Supported
Free Trial
Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Supported
In Person
Not Supported
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Company InformationAnyscale
Founded: 2019
United States
ray.io
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Company InformationWeights & Biases
Founded: 2017
United States
wandb.ai/site
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Alternatives |
Alternatives |
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Categories |
Categories |
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Integrations
TensorFlow
Supported
Amazon EC2 Trn2 Instances
Supported
Amazon SageMaker
Supported
Amazon Web Services (AWS)
Supported
Anyscale
Supported
Apache Airflow
Supported
Azure Kubernetes Service (AKS)
Supported
Cuckoo
Not Supported
Dask
Supported
Databricks
Supported
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Integrations
TensorFlow
Supported
Amazon EC2 Trn2 Instances
Not Supported
Amazon SageMaker
Not Supported
Amazon Web Services (AWS)
Not Supported
Anyscale
Not Supported
Apache Airflow
Not Supported
Azure Kubernetes Service (AKS)
Not Supported
Cuckoo
Supported
Dask
Not Supported
Databricks
Not Supported
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