Open Source C# Data Analytics Tools

.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. 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.

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.

BigBang/Horizon is a proteomics data analysis pipeline with focus on the shotgun LC/MSMS workflow.

CANStream is a .NET application intended to be used for CAN (Controller Area Network) bus communication development, testing and validation. CANStream allows to extensively test any system using CAN communication by sending and receiving CAN frames. Thanks to its powerful built-in mathematical expression evaluator, CANStream can also behave as a real control system feeding back the test device or commanding a third party device with context sensible data. Extended data logging and data analysis features of CANStream provide a comprehensive solution for testing and results analysis CANStream extensively uses the PCAN-Basic API developed by PEAK System for the PCAN-USB adapter You will therefore need to have PCAN-USB adapter and at least one free USB port available to make a complete use of CANStream. CANStream can manage up to eight PCAN-USB adapters at the same time, thus you will need eight USB ports available.

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.

DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify JASP for advanced data editing and RapidMiner for advanced prediction modeling. DSTK is written in C#, Java and Python to interface with R, NLTK, and Weka. It can be expanded with plugins using R Scripts. We have also created plugins for more statistical functions, and Big Data Analytics with Microsoft Azure HDInsights (Spark Server) with Livy. License: R, RStudio, NLTK, SciPy, SKLearn, MatPlotLib, Weka, ... each has their own licenses.

Changelog (Version 7 - Update 1) New Discard Partialy Changes New Edit Row in Window New List of User Connections New Show Image on Form New Quickly View of Cell Values Download also : 1) ETU SQL for MySQL: https://sourceforge.net/projects/etusqlformysql/ 2) ETU SQL for Oracle: https://sourceforge.net/projects/etusqlfororacle/ 3) ETU SQL for DB2: https://sourceforge.net/projects/etusqlfordb2/ 4) ETU SQL for PostgreSQL: https://sourceforge.net/projects/etusqlforpostgreSQL/

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.

HCS Analyzer is an open source software dedicated to High Content Screening data processing and analysis.

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

A tool to support data-analysis on a Oracle-DB. In Greek mythology, Metis (Μῆτις) was of the Titan generation ... The Stoic commentators allegorized Metis as the embodiment of "wisdom" or "wise counsel" ... (from Wikipadia)

PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels of spectra, peptides and proteins, PANDA works out a few quantitative filters and new scores for quantification confidence. Third, PANDA is designed for processing proteomics big data in parallel.

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.

This project consists out of a windows based designer application and a library (that can run on multiple platforms, including android) together with several demo applications (including an MVC3 chatbot client and an android application). It is probably best compared to a database management system, but for neural networks instead of relational data. As such, the library is optimized for handling any type of data-size by using advanced streaming and caching algorithms. With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,...