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  2. Online machine learning - Wikipedia

    en.wikipedia.org/wiki/Online_machine_learning

    e. In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once.

  3. Massive open online course - Wikipedia

    en.wikipedia.org/wiki/Massive_open_online_course

    A massive open online course ( MOOC / muːk /) or an open online course is an online course aimed at unlimited participation and open access via the Web. [1] In addition to traditional course materials, such as filmed lectures, readings, and problem sets, many MOOCs provide interactive courses with user forums or social media discussions to ...

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

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

    In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets. The model is initially fit on a training data set, [3] which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. [4]

  5. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    The data is known as training data, and consists of a set of training examples. Each training example has one or more inputs and the desired output, also known as a supervisory signal. In the mathematical model, each training example is represented by an array or vector, sometimes called a feature vector, and the training data is represented by ...

  6. Rapid learning - Wikipedia

    en.wikipedia.org/wiki/Rapid_learning

    Rapid learning. Rapid learning (or Rapid eLearning Development) has traditionally referred to a methodology to build e-learning courses rapidly. [1] Typically the author will create slides in PowerPoint, record audio and video narration on top of the slides, and then use software to add tests, or even collaboration activities between the slides.

  7. k-nearest neighbors algorithm - Wikipedia

    en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    k. -nearest neighbors algorithm. In statistics, the k-nearest neighbors algorithm ( k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, [1] and later expanded by Thomas Cover. [2] It is used for classification and regression. In both cases, the input consists of the k closest training ...

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