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Source channel @githubtrending · Post #14998 · Jul 26

#java#keycloak#oidc#saml Keycloak is an open-source tool that helps you add secure login and access control to your apps easily. It lets users sign in once and access many applications without logging in repeatedly (single sign-on). You don’t have to manage user data or authentication yourself because Keycloak handles it all securely using industry standards like OAuth 2.0 and SAML. It supports strong security features like two-factor authentication and works well with many identity providers. This saves you time and money by avoiding custom solutions and simplifies managing user access across your services. You can run it on your own servers or in the cloud, and it’s easy to set up and customize[1][2][3][4][5]. https://github.com/keycloak/keycloak

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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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