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  2. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    v. t. e. In machine learning, the perceptron (or McCulloch–Pitts neuron) is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. [ 1]

  3. Multilayer perceptron - Wikipedia

    en.wikipedia.org/wiki/Multilayer_perceptron

    v. t. e. A multilayer perceptron ( MLP) is a name for a modern feedforward artificial neural network, consisting of fully connected neurons with a nonlinear activation function, organized in at least three layers, notable for being able to distinguish data that is not linearly separable. [ 1]

  4. Perceptrons (book) - Wikipedia

    en.wikipedia.org/wiki/Perceptrons_(book)

    Perceptrons: an introduction to computational geometry is a book written by Marvin Minsky and Seymour Papert and published in 1969. An edition with handwritten corrections and additions was released in the early 1970s. An expanded edition was further published in 1988 ( ISBN 9780262631112) after the revival of neural networks, containing a ...

  5. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    v. t. e. In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [ 1][ 2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain.

  6. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] [18] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  7. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". [1] Text is converted to numerical representations called tokens , and each token is converted into a vector via looking up from a word embedding table. [ 1 ]

  8. Mathematics of paper folding - Wikipedia

    en.wikipedia.org/wiki/Mathematics_of_paper_folding

    Mathematics of paper folding. Map folding for a 2×2 grid of squares: there are eight different ways to fold such a map along its creases. The discipline of origami or paper folding has received a considerable amount of mathematical study. Fields of interest include a given paper model's flat-foldability (whether the model can be flattened ...

  9. Programming as craft | TechCrunch

    techcrunch.com/2018/02/24/programming-as-craft

    It is a push to think about permanence, on how to write code that can stand up for years to come. Ultimately, it is a request to think in terms of creating a field that makes us more human in ...

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