Showing 2 open source projects for "framework python"

View related business solutions
  • Build Securely on AWS with Proven Frameworks Icon
    Build Securely on AWS with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
    Download Now
  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
    Start Free
  • 1
    Archipelago

    Archipelago

    Archipelago Multi-Game Randomizer and Server

    Archipelago is an open-source multi-game randomizer framework that allows multiple players to play different games simultaneously while sharing a unified item randomization system. The software creates what is known as a “multiworld,” where items that normally appear in one game may instead appear in another player’s game. When a player finds an item belonging to someone else, the system automatically sends that item to the correct player through a networked server. This design encourages...
    Downloads: 18 This Week
    Last Update:
    See Project
  • 2
    DreamerV3

    DreamerV3

    Mastering Diverse Domains through World Models

    DreamerV3 is an open-source implementation of a reinforcement learning algorithm that uses world models to train intelligent agents capable of learning complex behaviors across many environments. The system works by building an internal model of the environment and then using that model to simulate possible future outcomes of actions, allowing the agent to learn from imagined experiences rather than only from real interactions. This approach enables the algorithm to efficiently learn...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next