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Wolfram Mathematica is a software system with built-in libraries for several areas of technical computing that allows machine learning, statistics, symbolic computation, data manipulation, network analysis, time series analysis, NLP, optimization, plotting functions and various types of data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in ...
Models developed in Model Center can be simulated in the Simulation Center. The software also provides a tight integration with the Mathematica environment. Users can develop, simulate, document, and analyze their Wolfram System Modeler models within Mathematica notebooks. The software is used in the engineering field as well as in the life ...
Free replacement for SPSS. QtiPlot: GUI, Python: proprietary: No 2004: May 31, 2017 / 0.9.9.11: Linux, Mac, Windows: Python scriptable R: Third party: GPL: Yes 1993: July 2, 2018 / 3.5.1("Feather Spray") Linux, Mac, Windows: In addition to base graphics, has a large number of graphics packages including lattice and ggplot2. [7] Interoperabile ...
Free modified BSD license: Full-featured general purpose CAS. Especially strong at symbolic integration. GAP: GAP Group 1986 1986 4.13.1: 13 June 2024 [10] Free GNU GPL [11] Specialized CAS for group theory and combinatorics. GeoGebra CAS: Markus Hohenwarter et al. 2013 6.0.753.0: 3 January 2023: Free for non-commercial use [12] Freeware [12]
You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses ...
Statistica 5.0 was released in 1995. It ran on both the new 32-bit Windows 95/NT and the previous 16-bit version, Windows 3.1. It featured many new statistics and graphics procedures, a word-processor-style output editor (combining tables and graphs), and a built-in development environment that enabled the user to easily design new procedures ...
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
A mathematical constant is a key number whose value is fixed by an unambiguous definition, often referred to by a symbol (e.g., an alphabet letter), or by mathematicians' names to facilitate using it across multiple mathematical problems. [1]