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  2. Metamodeling - Wikipedia

    en.wikipedia.org/wiki/Metamodeling

    A metamodel is a model of a model, and metamodeling is the process of generating such metamodels. Thus metamodeling or meta-modeling is the analysis, construction, and development of the frames, rules, constraints, models, and theories applicable and useful for modeling a predefined class of problems. As its name implies, this concept applies ...

  3. Meta-learning (computer science) - Wikipedia

    en.wikipedia.org/wiki/Meta-learning_(computer...

    Meta learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing learning ...

  4. Meta-learning - Wikipedia

    en.wikipedia.org/wiki/Meta-learning

    Meta-learning. Meta-learning is a branch of metacognition concerned with learning about one's own learning and learning processes. The term comes from the meta prefix's modern meaning of an abstract recursion, or "X about X", similar to its use in metaknowledge, metamemory, and meta-emotion .

  5. Coursera - Wikipedia

    en.wikipedia.org/wiki/Coursera

    Coursera Inc. (/ k ər ˈ s ɛ r ə /) is an American global massive open online course provider. It was founded in 2012 by Stanford University computer science professors Andrew Ng and Daphne Koller. Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects.

  6. Meta AI - Wikipedia

    en.wikipedia.org/wiki/Meta_AI

    Meta AI is an American artificial intelligence laboratory owned by Meta Platforms Inc. (formerly known as Facebook, Inc.), Meta AI develops various forms of artificial intelligence, including augmented and artificial reality technologies. It is also an academic research laboratory focused on generating knowledge for the AI community.

  7. Model order reduction - Wikipedia

    en.wikipedia.org/wiki/Model_order_reduction

    Model order reduction aims to lower the computational complexity of such problems, for example, in simulations of large-scale dynamical systems and control systems. By a reduction of the model's associated state space dimension or degrees of freedom, an approximation to the original model is computed which is commonly referred to as a reduced ...

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