Showing 3 open source projects for "machine learning platform"

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    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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  • 1
    xiaohongshu-ops

    xiaohongshu-ops

    Turn Openclaw into a Xiaohongshu operations assistant

    xiaohongshu-ops-skill is a curated repository focused on operational strategies, growth techniques, and content optimization practices for the Xiaohongshu platform, also known as RED, which is widely used for social commerce and influencer marketing. Unlike traditional software projects, it functions as a structured knowledge base that compiles actionable insights for content creators, marketers, and businesses aiming to grow their presence on the platform. The repository includes guides on...
    Downloads: 0 This Week
    Last Update:
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  • 2
    Compound Engineering

    Compound Engineering

    Official Compound Engineering plugin for Claude Code, Codex, Cursor

    The Compound Engineering plugin project is an AI-driven workflow system designed to improve software development by turning each unit of work into a reusable and compounding asset. It provides a structured set of commands and agents that guide developers through stages such as brainstorming, planning, execution, review, and knowledge capture. The core philosophy is to reduce technical debt by emphasizing thorough planning and continuous learning, ensuring that each iteration improves future...
    Downloads: 9 This Week
    Last Update:
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  • 3
    anti-distill

    anti-distill

    Anti-distillation for employee Skills

    anti-distill is a research-oriented project focused on protecting machine learning models from knowledge distillation attacks, where smaller models attempt to replicate the behavior of larger proprietary systems. The project explores techniques that make it harder for external models to learn from outputs, thereby preserving intellectual property and model uniqueness. It likely introduces methods such as output perturbation, watermarking, or response shaping to prevent accurate imitation. ...
    Downloads: 1 This Week
    Last Update:
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