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  2. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is "a concept to unify statistics, data analysis, informatics, and their related methods " to "understand and analyze actual phenomena " with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. [6]

  3. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...

  4. Data (computer science) - Wikipedia

    en.wikipedia.org/wiki/Data_(computer_science)

    In computer science, data (treated as singular, plural, or as a mass noun) is any sequence of one or more symbols; datum is a single symbol of data. Data requires interpretation to become information. Digital data is data that is represented using the binary number system of ones (1) and zeros (0), instead of analog representation.

  5. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis. Tukey's championing of EDA encouraged the development of statistical computing packages, especially S ...

  6. Analytics - Wikipedia

    en.wikipedia.org/wiki/Analytics

    Analytics. Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.

  7. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    Precision and recall. In pattern recognition, information retrieval, object detection and classification (machine learning), precision and recall are performance metrics that apply to data retrieved from a collection, corpus or sample space. Precision (also called positive predictive value) is the fraction of relevant instances among the ...

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