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What is Sumocode?

Creating applications and games has become remarkably accessible, enabling you to dive into coding with just a few simple lines of code while learning through fun, gamified examples. You have the flexibility to remix existing code samples or craft entirely new creations, and by leveraging JavaScript, you'll soon discover how easy it can be to develop games with minimal hassle. Unlock your creative potential with Sumocode, a platform that encourages innovation and the design of unique projects! No matter your age—whether you're 5, 55, or even 105—this journey into coding is open to everyone, allowing you to enhance your skill set and acquire valuable programming abilities. Sumocode is specifically tailored to help you navigate the early phases of becoming a programmer, demonstrating that the coding process is more approachable than many might think. You'll master the art of assembling apps and writing code snippets effortlessly, especially with the support of our Sumo3D code library, which serves as a robust foundation for your projects. The choice is yours: you can either expand on our provided examples or start fresh, paving the way for limitless opportunities in your coding pursuits. Step into the exciting realm of programming and explore the endless possibilities that await you as your creativity blossoms! Embrace the adventure, and watch as your skills grow and develop along the way!

What is Ray?

You can start developing on your laptop and then effortlessly scale your Python code across numerous GPUs in the cloud. Ray transforms conventional Python concepts into a distributed framework, allowing for the straightforward parallelization of serial applications with minimal code modifications. With a robust ecosystem of distributed libraries, you can efficiently manage compute-intensive machine learning tasks, including model serving, deep learning, and hyperparameter optimization. Scaling existing workloads is straightforward, as demonstrated by how Pytorch can be easily integrated with Ray. Utilizing Ray Tune and Ray Serve, which are built-in Ray libraries, simplifies the process of scaling even the most intricate machine learning tasks, such as hyperparameter tuning, training deep learning models, and implementing reinforcement learning. You can initiate distributed hyperparameter tuning with just ten lines of code, making it accessible even for newcomers. While creating distributed applications can be challenging, Ray excels in the realm of distributed execution, providing the tools and support necessary to streamline this complex process. Thus, developers can focus more on innovation and less on infrastructure.

Media

Media

Integrations Supported

Python
C++
HTML
Java
JavaScript

Integrations Supported

Python
Amazon EC2 Trn2 Instances
Amazon SageMaker
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks
Feast
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
LanceDB
MLflow
PyTorch
Snowflake
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

$9 per month
Free Version

Pricing Information

Free
Open source. Consumption-based.
Free Version
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Sumo Apps

Company Location

Finland

Company Website

sumo.app/sumocode

Company Facts

Organization Name

Anyscale

Date Founded

2019

Company Location

United States

Company Website

ray.io

Categories and Features

Code Editors

Not specified

Categories and Features

Deep Learning

Not specified

Machine Learning

Not specified

ML Model Deployment

Not specified

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