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  2. Moravec's paradox - Wikipedia

    en.wikipedia.org/wiki/Moravec's_paradox

    Moravec's paradox is the observation in the fields of artificial intelligence and robotics that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception skills require enormous computational resources.

  3. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]

  4. Multi-task learning - Wikipedia

    en.wikipedia.org/wiki/Multi-task_learning

    Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. This can result in improved learning efficiency and prediction accuracy for the task-specific models, when compared to training the models separately.

  5. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  6. Computational thinking - Wikipedia

    en.wikipedia.org/wiki/Computational_thinking

    The history of computational thinking as a concept dates back at least to the 1950s but most ideas are much older. [6] [3] Computational thinking involves ideas like abstraction, data representation, and logically organizing data, which are also prevalent in other kinds of thinking, such as scientific thinking, engineering thinking, systems thinking, design thinking, model-based thinking, and ...

  7. Anaconda (Python distribution) - Wikipedia

    en.wikipedia.org/wiki/Anaconda_(Python_distribution)

    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 ...

  8. Zed Shaw - Wikipedia

    en.wikipedia.org/wiki/Zed_Shaw

    Nonetheless, in February 2017 he published a first draft of Learn Python 3 The Hard Way. [9] [better source needed] He stated in November 2016 that "Python 3 is not Turing complete" due to claims from Python project developers that Python 2 code cannot be made to run in the Python 3 VM. [10] This statement has drawn a lot of criticism. [11]

  9. Spaced repetition - Wikipedia

    en.wikipedia.org/wiki/Spaced_repetition

    Each succeeding group has a longer period of time before the learner is required to revisit the cards. In Leitner's original method, published in his book So lernt man Lernen (How To Learn To Learn), the schedule of repetition was governed by the size of the partitions in the learning box. These were 1, 2, 5, 8 and 14 cm.