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Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.
This is a list of free and open-source software (FOSS) packages, computer software licensed under free software licenses and open-source licenses.Software that fits the Free Software Definition may be more appropriately called free software; the GNU project in particular objects to their works being referred to as open-source. [1]
Orange: A component-based data mining and machine learning software suite written in the Python language. PSPP: Data mining and statistics software under the GNU Project similar to SPSS; R: A programming language and software environment for statistical computing, data mining, and graphics. It is part of the GNU Project.
KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.
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Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License.It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques".
While the analysis of educational data is not itself a new practice, recent advances in educational technology, including the increase in computing power and the ability to log fine-grained data about students' use of a computer-based learning environment, have led to an increased interest in developing techniques for analyzing the large amounts of data generated in educational settings.
Course developers could charge licensing fees for educational institutions that use its materials. Introductory or "gateway" courses and some remedial courses may earn the most fees. Free introductory courses may attract new students to follow-on fee-charging classes. Blended courses supplement MOOC material with face-to-face instruction.