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software.intel.com /content /www /us /en /develop /tools /data-analytics-acceleration-library.html oneAPI Data Analytics Library (oneDAL; formerly Intel Data Analytics Acceleration Library or Intel DAAL), is a library of optimized algorithmic building blocks for data analysis stages most commonly associated with solving Big Data problems.
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. [2]
jamovi (stylised in all lower-case) is a free and open-source computer program for data analysis and performing statistical tests. The core developers of jamovi are Jonathon Love, Damian Dropmann, and Ravi Selker, who were developers for the JASP project.
Wes McKinney is an American software developer and businessman. He is the creator and "Benevolent Dictator for Life" (BDFL) of the open-source pandas package for data analysis in the Python programming language, and has also authored three versions of the reference book Python for Data Analysis.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Python library for the manipulation and storage of a wide range of geoscientific data (points, curve, surface, 2D and 3D grids) in geoh5 file format, natively supported by Geoscience ANALYST free 3D viewer Mira Geoscience Ltd. LPGL 3.0 Cross-platform: Python: Documentation and tutorials fully available in ReadTheDocs: geoapps repository [24]
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
Anaconda is a distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. Anaconda distribution includes data-science packages suitable for Windows, Linux, and macOS ...