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  2. Master in Data Science - Wikipedia

    en.wikipedia.org/wiki/Master_in_Data_Science

    When Harvard Business Review called data scientist "The Sexiest Job of the 21st Century" the term became a buzzword, [4] and is now often applied to business analytics, or even arbitrary use of data, or used as a term for statistics. While many university programs now offer a data science degree, there exists no consensus on a definition or ...

  3. List of professional designations in the United States

    en.wikipedia.org/wiki/List_of_professional...

    Senior Living Certification Commission (SLCC) is a nonprofit corporation, autonomous from Argentum, with its own governing Board of Commissioners. SLCC offers a voluntary certification program for assisted living executive directors. Certified Healthcare Simulation Educator: CHSE Society for Simulation in Healthcare

  4. SVKM's NMIMS - Wikipedia

    en.wikipedia.org/wiki/SVKM's_NMIMS

    It includes courses on artificial intelligence, machine learning, and big data analytics, aiming to prepare students for roles that require data-driven decision-making. The curriculum emphasizes practical training through industry projects and internships, focusing on the application of analytical tools in business contexts. [13]

  5. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Boost Software License: Yes Cross-platform: C++: C++, Python: Yes No Yes No Yes Yes No Yes Yes Yes Yes Flux: Mike Innes 2017 MIT license: Yes Linux, MacOS, Windows (Cross-platform) Julia: Julia: Yes No Yes Yes [13] Yes Yes No Yes Yes Intel Data Analytics Acceleration Library: Intel 2015 Apache License 2.0: Yes Linux, macOS, Windows on Intel CPU ...

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

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