Showing 6 open source projects for "open source assembly software source code"

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  • Auth0 B2B Essentials: SSO, MFA, and RBAC Built In Icon
    Auth0 B2B Essentials: SSO, MFA, and RBAC Built In

    Unlimited organizations, 3 enterprise SSO connections, role-based access control, and pro MFA included. Dev and prod tenants out of the box.

    Auth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
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  • 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.
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  • 1
    DVC Extension for Visual Studio Code

    DVC Extension for Visual Studio Code

    https://github.com/iterative/vscode-dvc

    A Visual Studio Code extension that integrates Data Version Control (DVC) into the development environment, enhancing reproducibility and collaboration for machine learning projects.
    Downloads: 1 This Week
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  • 2
    Deepnote

    Deepnote

    Deepnote is a drop-in replacement for Jupyter

    Deepnote is an open-source collaborative data science notebook platform designed as a modern alternative to traditional Jupyter notebooks. The project provides an AI-first computational environment where users can write, analyze, and share code, data, and visualizations in a single integrated workspace. Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. ...
    Downloads: 0 This Week
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  • 3
    Responsible AI Toolbox

    Responsible AI Toolbox

    Responsible AI Toolbox is a suite of tools providing model

    Responsible AI Toolbox is a software framework designed to help developers evaluate and improve the reliability, fairness, and transparency of machine learning systems. The project provides tools that assist in analyzing model behavior, detecting bias, improving robustness, and explaining predictions produced by AI systems. It is designed to integrate with common machine learning frameworks, especially PyTorch, allowing developers to apply responsible AI techniques within existing workflows....
    Downloads: 1 This Week
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  • 4
    Mintlify Writer

    Mintlify Writer

    AI powered documentation writer

    Writing documentation sucks. Let Mintlify take care of it. Just highlight code and see the magic.
    Downloads: 0 This Week
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  • Forever Free Full-Stack Observability | Grafana Cloud Icon
    Forever Free Full-Stack Observability | Grafana Cloud

    Our generous forever free tier includes the full platform, including the AI Assistant, for 3 users with 10k metrics, 50GB logs, and 50GB traces.

    Built on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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  • 5
    TensorFlow.js models

    TensorFlow.js models

    Pretrained models for TensorFlow.js

    This repository hosts a set of pre-trained models that have been ported to TensorFlow.js. The models are hosted on NPM and unpkg so they can be used in any project out of the box. They can be used directly or used in a transfer learning setting with TensorFlow.js. To find out about APIs for models, look at the README in each of the respective directories. In general, we try to hide tensors so the API can be used by non-machine learning experts. New models should have a test NPM script. You...
    Downloads: 1 This Week
    Last Update:
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  • 6
    Facets

    Facets

    Visualizations for machine learning datasets

    The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. Explore Facets Overview and Facets Dive on the UCI Census Income...
    Downloads: 0 This Week
    Last Update:
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