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Source channel @githubtrending · Post #14900 · Jul 2

#c_lang#cryptography#decryption#encryption#openssl#ssl#tls OpenSSL is a free, open-source toolkit that helps secure data by using strong encryption methods like TLS, SSL, and QUIC protocols. It includes libraries for cryptography and a command-line tool to create keys, certificates, encrypt data, and test security. OpenSSL is widely trusted and used by many software and websites to protect sensitive information during transmission, ensuring privacy and data integrity. It works on many operating systems and is regularly updated by a global community. Using OpenSSL helps you build secure applications and protect communications from cyber threats easily and reliably[1][3][5]. https://github.com/openssl/openssl

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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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