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Source channel @githubtrending · Post #14937 · Jul 9

#typescript#api#cms#cms_framework#content_management#content_management_system#customizable#dashboard#graphql#hacktoberfest#headless_cms#jamstack#javascript#koa#koa2#mysql#no_code#nodejs#rest#strapi#typescript Strapi is a free, open-source headless content management system that lets you manage content easily and flexibly, whether you host it yourself or use Strapi Cloud. It works with many databases and lets you build custom APIs, routes, and plugins to fit your needs. You can use any frontend technology you like, such as React, Vue, or Angular, and it comes with a modern, customizable admin panel. Strapi is fast, secure, and scalable, making it simple to deliver content across websites, apps, or devices. This means you get full control over your content and how it’s displayed, saving time and effort while keeping your project future-proof[1][2][3]. https://github.com/strapi/strapi

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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