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1. docs.ray.io › en › latestWelcome to Ray! — Ray 2.23.0

   docs.ray.io › en › latest

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   Welcome to Ray. An open source framework to build and scale your ML and Python applications easily. Get started with Ray. Install Ray. Ray Example Gallery.

2. de.wikipedia.org › wiki › RayRay – Wikipedia

   de.wikipedia.org › wiki › Ray

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   Ray. Ray steht für: Ray (Familienname), Familienname. Ray (Vorname), Vorname. Ray (Roboter), Park-Roboter. Ray (Zeitschrift), österreichisches Filmmagazin. Ray (Film), US-amerikanischer Film von Taylor Hackford (2004) Ray, Abkürzung für Bookray beim Bookcrossing. The Ray, amerikanische Comicserie.

3. github.com › ray-project › rayGitHub - ray-project/ray: Ray is a unified framework for scaling...

   github.com › ray-project › ray

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   Monitor and debug Ray applications and clusters using the Ray dashboard. Ray runs on any machine, cluster, cloud provider, and Kubernetes, and features a growing ecosystem of community integrations. Install Ray with: pip install ray. For nightly wheels, see the Installation page.

4. docs.ray.io › en › latestRay Tune: Hyperparameter Tuning — Ray 2.23.0

   docs.ray.io › en › latest

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   Ray Tune: Hyperparameter Tuning. #. Tune is a Python library for experiment execution and hyperparameter tuning at any scale. You can tune your favorite machine learning framework ( PyTorch, XGBoost, TensorFlow and Keras, and more) by running state of the art algorithms such as Population Based Training (PBT) and HyperBand/ASHA .

5. www.amazon.de › Ray-Jamie-Foxx › dpAmazon.de: Ray ansehen | Prime Video

   www.amazon.de › Ray-Jamie-Foxx › dp

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   Drama · Sanft · Inspirierend · Berührend. Als Kauf- oder Leihtitel verfügbar. Leihen. HD 3,99 €. Kaufen. HD 8,99 €. Weitere. Kaufoptionen. Bei geliehenen Titeln hast du 30 Tage Zeit, um das Video erstmals wiederzugeben, und anschließend 48 Stunden, um es vollständig anzusehen.

6. docs.ray.io › en › latestGetting Started — Ray 2.23.0

   docs.ray.io › en › latest

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   Getting Started. #. Use Ray to scale applications on your laptop or the cloud. Choose the right guide for your task. Scale ML workloads: Ray Libraries Quickstart. Scale general Python applications: Ray Core Quickstart. Deploy to the cloud: Ray Clusters Quickstart. Debug and monitor applications: Debugging and Monitoring Quickstart.

7. www.ray.ioProductionizing and scaling Python ML workloads simply | Ray

   www.ray.io

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   Powered by Ray. "One of the biggest problems that Ray helped us resolve is improving scalability, latency, and cost-efficiency of very large workloads. We were able to improve the scalability by an order of magnitude, reduce the latency by over 90%, and improve the cost efficiency by over 90%. It was financially infeasible for us to approach ...