Search Results for "linux-bullseye"
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Showing 7 open source projects for "linux-bullseye"
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
...This means you can use .NET for Apache Spark anywhere you write .NET code allowing you to reuse all the knowledge, skills, code, and libraries you already have as a .NET developer. .NET for Apache Spark runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. It also runs on all major cloud providers including Azure HDInsight Spark, Amazon EMR Spark, AWS & Azure Databricks. -
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ProteoWizard development moved to GitHub in 2018. The ProteoWizard Library is a set of software libraries and tools for rapid development of proteomics data analysis software. The libraries are cross-platform and built from the ground up using modern C++ techniques.
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HCS Analyzer
High Content Screening Analyzer
HCS Analyzer is an open source software dedicated to High Content Screening data processing and analysis. -
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FoodPhysicsApplication
A C# application for scientists in the area of physical chemistry
The project has been created to develop a software that can help scientists in the area of physical chemistry with focus on foods data analysis tools that are currently mainly done by hand. In the first step, advanced analysis of texture analyzer compression data are provided and the project will be extended over time dependent on the time I can get to continue with it. -
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Logbus-ng consists in a set of tools to aid developers perform Log Analysis in all the stages: log generation, collection, distribution, storage and analysis. It is designed specifically for Field Failure Data Analysis in critical distributed systems
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SODA is short for School Online Data Analysis. The project's aim is to simplify the process of undertaking meaningful data analysis at both the departmental and whole school curriculum levels.
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The Canopy project is an initiative to merge and expand the functionality of Perl-speaks-NONMEM (PsN), Census, Xpose and PopED. The goal is to produce a coherent, inclusive and convenient platform for pharmacometric data analysis.
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