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7 repositorios

Awesome GitHub RepositoriesCloud Execution Environments

Platforms that provide remote, containerized runtimes for executing code directly in a web browser.

Distinguishing note: Focuses on browser-based execution rather than general infrastructure management.

Explore 7 awesome GitHub repositories matching devops & infrastructure · Cloud Execution Environments. Refine with filters or upvote what's useful.

Awesome Cloud Execution Environments GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • vercel-labs/agent-browserAvatar de vercel-labs

    vercel-labs/agent-browser

    36,203Ver en GitHub↗

    This project is an agentic framework designed to enable autonomous web navigation and browser automation. It functions as a controller that translates natural language instructions into deterministic browser actions, allowing agents to interact with websites, perform data extraction, and manage complex authentication flows. By leveraging accessibility trees and semantic element resolution, the framework mimics human-like navigation, moving beyond brittle DOM selectors to interact reliably with modern web interfaces. The framework distinguishes itself through its focus on secure, scalable exec

    Provides platforms that provide remote, containerized runtimes for executing code directly in a web browser.

    Rust
    Ver en GitHub↗36,203
  • norvig/pytudesAvatar de norvig

    norvig/pytudes

    24,271Ver en GitHub↗

    Provides direct integration with cloud-based runtimes for executing code snippets in the browser.

    Jupyter Notebookdemonstrate-skillspracticeprogramming
    Ver en GitHub↗24,271
  • ageron/handson-ml3Avatar de ageron

    ageron/handson-ml3

    13,463Ver en GitHub↗

    This repository serves as a comprehensive educational resource for mastering machine learning and deep learning through a series of interactive Jupyter Notebooks. It provides a structured collection of tutorials and code examples designed to guide users through the fundamental and advanced techniques of the Python data science ecosystem. The project distinguishes itself by offering hands-on exercises that demonstrate the full lifecycle of machine learning projects. Users can explore end-to-end data pipelines, ranging from initial data loading and preprocessing to the training and deployment o

    Provides remote, browser-based execution environments for running machine learning code without local configuration.

    Jupyter Notebook
    Ver en GitHub↗13,463
  • hangtwenty/dive-into-machine-learningAvatar de hangtwenty

    hangtwenty/dive-into-machine-learning

    11,395Ver en GitHub↗

    This project is a comprehensive collection of machine learning educational resources, featuring a Python-based curriculum, study guides for deep learning, and a specialized knowledge base for machine learning operations. It provides structured learning paths that guide users from foundational programming through to advanced neural network implementations. The repository focuses on interactive learning by providing a directory of executable notebooks and cloud-hosted experiments. It maps theoretical research papers and textbooks to practical code implementations and maintains a curated directo

    Provides links to remote, browser-based environments for executing machine learning code without local setup.

    Ver en GitHub↗11,395
  • moesnow/march7thassistantAvatar de moesnow

    moesnow/March7thAssistant

    10,800Ver en GitHub↗

    崩坏:星穹铁道全自动 三月七小助手

    Operates automation in the background without a visible window or inside a Docker container for remote execution.

    Pythonhonkai-star-railstar-rail
    Ver en GitHub↗10,800
  • mitdeeplearning/introtodeeplearningAvatar de MITDeepLearning

    MITDeepLearning/introtodeeplearning

    8,702Ver en GitHub↗

    This repository contains the lab materials and Jupyter notebooks for MIT's introductory deep learning course, using TensorFlow and Keras for hands-on exercises. The courseware is delivered as pre-configured notebooks that run on Google Colaboratory's cloud infrastructure, eliminating the need for local software installation. Learners can toggle the Colab runtime to a GPU-backed hardware accelerator for faster neural network training during lab exercises. A shared Python package provides helper functions that standardize common operations across all notebooks. The course guides students throug

    Provides pre-configured Jupyter notebooks that run entirely on Google Colaboratory's cloud infrastructure.

    Jupyter Notebookcomputer-visiondeep-learningdeep-reinforcement-learning
    Ver en GitHub↗8,702
  • turbot/steampipeAvatar de turbot

    turbot/steampipe

    7,701Ver en GitHub↗

    Steampipe is a cloud infrastructure query engine and API-to-SQL mapper that translates REST and GraphQL API responses into relational rows and columns. It allows for the retrieval and joining of real-time data from multiple cloud service providers using a relational database interface. The project functions as a PostgreSQL foreign data wrapper and an SQLite API extension, mapping external API endpoints to virtual tables. This enables the use of standard SQL to query live cloud services and aggregate data from different providers and service accounts into a single unified dataset. The system

    Enables executing SQL queries against cloud resources from browser-based terminal environments.

    Goawsazurecis
    Ver en GitHub↗7,701
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