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Übung: automatische Tests durch Continuous Integration mit Forschungsdaten und Publikationsdaten
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Übung: automatische Tests durch Continuous Integration mit Forschungsdaten und Publikationsdaten
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Übung: automatische Tests durch Continuous Integration mit Forschungsdaten und Publikationsdaten
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Benjamin Paaßen / relational_neural_gas
GNU General Public License v3.0 or laterThis is an implementation of the Neural Gas algorithm on distance data (Relational Neural Gas) for unsupervised clustering.
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Benjamin Paaßen / median_distance_glvq
GNU General Public License v3.0 or laterMedian Distance Generalized Learning Vector Quantization is a classification algorithm for distance data where data is represented by prototypes and classification is done by assigning the label of the closest prototype.
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AMiRo / AMiRo-BLT
GNU General Public License v3.0 onlyThe bootloader toolchain for the microcontroller based modules of the Autonomous Mini Robot (AMiRo). It comprises the code for the microcontrollers as well as two according flashing tools and defines a system synchronization protocol (SSSP).
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AMiRo / AMiRo-OS
OtherThe operating system for the Autonomous Mini Robot (AMiRo). It is based on ChibiOS, but enhances it for more flexible use.
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AMiRo / AMiRo-Apps
OtherA collection of applications and configurations to be used in combination with AMiRo-OS and μRtWare.
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ECCB 2018 Tutorial #13: Modern and scalable tools for efficient analysis of very large metagenomic datasets. Please refer to http://eccb18.org/tutorial-13/ and https://eccb18-metagenomics-tutorial.readthedocs.io for details.
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Conquaire / conquaire-book
Creative Commons Attribution Non Commercial Share Alike 4.0 InternationalThe Conquaire Book
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Conquaire / quality_checks
BSD 3-Clause "New" or "Revised" LicenseUpdated -
Benjamin Paaßen / Python Edit Distances
GNU General Public License v3.0 onlyA library for edit distances in Python 3, based on the TCS Alignment Toolbox.
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Tilman Lüttje / Who is the Boss
MIT LicenseAbschlussprojekt 2019 - Netzwerk-Programmierung
http://bibiserv.cebitec.uni-bielefeld.de/resources/lehre/netprog19/Projekt_2019.pdf
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Übung: automatische Tests durch Continuous Integration mit Forschungsdaten und Publikationsdaten
Updated