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  2. Learning rule - Wikipedia

    en.wikipedia.org/wiki/Learning_rule

    Learning rule. An artificial neural network 's learning rule or learning process is a method, mathematical logic or algorithm which improves the network's performance and/or training time. Usually, this rule is applied repeatedly over the network. It is done by updating the weights and bias levels of a network when a network is simulated in a ...

  3. D2L - Wikipedia

    en.wikipedia.org/wiki/D2L

    D2L (or Desire2Learn) is a Canada-based global software company with offices in Australia, Brazil, Europe, Singapore, and the United States.. D2L is the developer of the Brightspace learning management system, a cloud-based software suite used by schools, higher educational institutions, and businesses for online and blended classroom learning.

  4. List of learning management systems - Wikipedia

    en.wikipedia.org/wiki/List_of_learning...

    Edmodo (closed in 2022) Elluminate (acquired by Blackboard in 2010) Learn.com (acquired by Taleo in 2010) PeopleSoft (acquired by Oracle in 2005) Plateau Systems (acquired by Successfactors in 2011) Softscape (acquired by SumTotal in 2010) SuccessFactors (acquired by SAP in 2012) SumTotal (acquired by Skillsoft in 2014)

  5. ADALINE - Wikipedia

    en.wikipedia.org/wiki/ADALINE

    The learning rule used by ADALINE is the LMS ("least mean squares") algorithm, a special case of gradient descent. Define the following notations: is the learning rate (some positive constant) is the output of the model; is the target (desired) output

  6. Delta College (Michigan) - Wikipedia

    en.wikipedia.org/wiki/Delta_College_(Michigan)

    Collectively, these stations are known as Delta College Public Media and they serve an audience of 1.2 million people in mid-Michigan. The college's student-run newspaper is the Delta Collegiate and has been published since the college opened in 1961. The newspaper prints a new issue every two weeks during the fall and winter semester.

  7. Stochastic gradient descent - Wikipedia

    en.wikipedia.org/wiki/Stochastic_gradient_descent

    Stochastic gradient descent is a popular algorithm for training a wide range of models in machine learning, including (linear) support vector machines, logistic regression (see, e.g., Vowpal Wabbit) and graphical models. [21] When combined with the back propagation algorithm, it is the de facto standard algorithm for training artificial neural ...

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