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Showing 3 open source projects for "custom"
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SDGym
Benchmarking synthetic data generation methods
... the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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ViennaCLBench
OpenCL linear algebra benchmark GUI for CPUs, GPUs, and MIC
ViennaCLBench provides a graphical user interface for collecting benchmark data for common OpenCL-accelerated linear algebra operations as implemented in the linear algebra library ViennaCL. -
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Big-Brother is a collection of J2EE filters and servlets that provide custom monitoring and auditing of web-applications, keeping track of who does what, when, and how often. It makes use of the jakarta-apache Struts framework for the interface GUI.
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