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  2. Timeline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Timeline_of_machine_learning

    Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s 'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s: Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach.

  3. The Alignment Problem - Wikipedia

    en.wikipedia.org/wiki/The_Alignment_Problem

    The Alignment Problem: Machine Learning and Human Values is a 2020 non-fiction book by the American writer Brian Christian.It is based on numerous interviews with experts trying to build artificial intelligence systems, particularly machine learning systems, that are aligned with human values.

  4. Hubert Dreyfus's views on artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Hubert_Dreyfus's_views_on...

    Book cover of the 1979 paperback edition. Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI, What Computers Can't Do (1972; 1979; 1992) and Mind over Machine, he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field.

  5. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  6. Computational economics - Wikipedia

    en.wikipedia.org/wiki/Computational_economics

    There are notable advantages and disadvantages of utilizing machine learning tools in economic research. In economics, a model is selected and analyzed at once. The economic research would select a model based on principle, then test/analyze the model with data, followed by cross-validation with other models.

  7. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]

  8. Data envelopment analysis - Wikipedia

    en.wikipedia.org/wiki/Data_envelopment_analysis

    Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...

  9. Business and management research - Wikipedia

    en.wikipedia.org/wiki/Business_and_management...

    Business and management research is a systematic inquiry that helps to solve business problems and contributes to management knowledge. It Is an applied research. Four factors (Easterby-Smith, 2008) combine to make business and management a distinctive focus for research : Transdiscipline approach