Search results
Results From The WOW.Com Content Network
Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature. treated for missing values, numerical attributes only, different percentages of anomalies, labels 1000+ files ARFF: Anomaly detection: 2016 (possibly updated with new datasets and/or results) [331] Campos et al.
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.
Notebook interfaces are widely used for statistics, data science, machine learning, and computer algebra. [ 2 ] At the notebook core is the idea of literate programming tools which "let you arrange the parts of a program in any order and extract documentation and code from the same source file.", [ 3 ] the notebook takes this approach to a new ...
Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]
The modern conception of data science as an independent discipline is sometimes attributed to William S. Cleveland. [23] In 2014, the American Statistical Association's Section on Statistical Learning and Data Mining changed its name to the Section on Statistical Learning and Data Science, reflecting the ascendant popularity of data science. [24]
Julia is a high-level, general-purpose [16] dynamic programming language, designed to be fast and productive, [17] for e.g. data science, artificial intelligence, machine learning, modeling and simulation, most commonly used for numerical analysis and computational science. [18] [19] [20]
Data science is a "concept to unify statistics, data analysis, machine learning, and their related methods" in order to "understand and analyze actual phenomena" with data. [136] It employs techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer science. data set. Also dataset.