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2. Orange (software) - Wikipedia

   en.wikipedia.org/wiki/Orange_(software)

   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.

3. Category : Free data and information visualization software

   en.wikipedia.org/wiki/Category:Free_data_and...

   Free and open-source software portal This is a category of articles relating to data visualization software which can be freely used, copied, studied, modified, and redistributed by everyone that obtains a copy: " free software " or " open source software ".

4. KNIME - Wikipedia

   en.wikipedia.org/wiki/KNIME

   Weka – machine-learning algorithms that can be integrated in KNIME; ELKI – data mining framework with many clustering algorithms; Keras - neural network library; Orange - an open-source data visualization, machine learning and data mining toolkit with a similar visual programming front-end; List of free and open-source software packages

5. List of information graphics software - Wikipedia

   en.wikipedia.org/wiki/List_of_information...

   A visual programming data-flow software suite with widgets for statistical data analysis, interactive data visualization, data mining, and machine learning. Origin: GUI, COM, C/ C++ and scripting: proprietary: No 1992: June 22, 2017 / 2017 SR2: Windows: Multi-layer 2D, 3D and statistical graphs for science and engineering. Built-in digitizing tool.

6. Data and information visualization - Wikipedia

   en.wikipedia.org/wiki/Data_and_information...

   Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...

7. Exploratory data analysis - Wikipedia

   en.wikipedia.org/wiki/Exploratory_data_analysis

   Exploratory data analysis is a technique to analyze and investigate a dataset and summarize its main characteristics. A main advantage of EDA is providing the visualization of data after conducting analysis. Tukey's championing of EDA encouraged the development of statistical computing packages, especially S at Bell Labs. [4]