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Source channel @githubtrending · Post #14660 · May 1

#go#containers#cyclonedx#docker#go#golang#hacktoberfest#oci#sbom#spdx#static_analysis#tool Syft is a tool that helps create a list of all the software components used in your applications, known as a Software Bill of Materials (SBOM). This list is important for finding vulnerabilities and ensuring that your software complies with licensing rules. By using Syft, you can better manage your software's security and compliance. It works with many types of software and can be used with other tools like Grype to check for vulnerabilities. This helps keep your software safe and up-to-date. https://github.com/anchore/syft

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#go #containers #cyclonedx #docker #golang #hacktoberfest #oci #sbom #spdx #static_analysis #tool

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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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#tfdeploy #numpy #machine_learning