Showing 4 open source projects for "machine learning python"

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  • 1
    workshops_project

    workshops_project

    Workshops is an open source, simple, dead-lightweight LMS

    Workshops is an open source, simple, dead-lightweight LMS (Learning Management System) application programmed in Python (version 3.8.x) with Django (version 2.2.x) web framework which main purpose is to make a standarized way to share knowledge via courses in a slide-based view in browser powered by remark javascript library, easy to create, edit, delete and show your courses using simple markdown and html if necessary.
    Downloads: 0 This Week
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  • 2
    Kore

    Kore

    Scalable and secure web application framework

    Kore is a web application platform for writing scalable, concurrent web-based processes in C or Python. It is built with a "secure by default" approach. It is fully privileged separated while using strong security features at the operating system level such as second, pledge, unveil, and more. Today Kore is used in a variety of applications ranging from high assurance cryptographic military devices, machine-learning stacks and even in the aerospace industry.
    Downloads: 1 This Week
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  • 3
    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django - Code Samples

    ...That was when I came up with the idea to create some comics along the text to illustrate some concepts and scenarios. I hope you enjoy the reading! Django is a Web framework written in Python. A Web framework is a software that supports the development of dynamic Web sites, applications, and services. It provides a set of tools and functionalities that solves many common problems associated with Web development.
    Downloads: 0 This Week
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  • 4
    Green Machine is a dynamic web content management system written in Python using Django web framework.
    Downloads: 0 This Week
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    Grafana: The open and composable observability platform

    Faster answers, predictable costs, and no lock-in built by the team helping to make observability accessible to anyone.

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