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  2. Predictive Model Markup Language - Wikipedia

    en.wikipedia.org/wiki/Predictive_Model_Markup...

    Predicted fields are those whose values are predicted by the model. Outlier Treatment (attribute outliers): defines the outlier treatment to be use. In PMML, outliers can be treated as missing values, as extreme values (based on the definition of high and low values for a particular field), or as is.

  3. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers, models, or metrics that can be used in native workflows in JAX, TensorFlow, or PyTorch — with one codebase."

  4. Neural network (machine learning) - Wikipedia

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

    The values of parameters are derived via learning. Examples of hyperparameters include learning rate, the number of hidden layers and batch size. [citation needed] The values of some hyperparameters can be dependent on those of other hyperparameters. For example, the size of some layers can depend on the overall number of layers. [citation needed]

  5. Transformer (deep learning architecture) - Wikipedia

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

    The number of neurons in the middle layer is called intermediate size (GPT), [56] filter size (BERT), [36] or feedforward size (BERT). [36] It is typically larger than the embedding size. For example, in both GPT-2 series and BERT series, the intermediate size of a model is 4 times its embedding size: =.

  6. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Arora et al. (2016) [25] explain word2vec and related algorithms as performing inference for a simple generative model for text, which involves a random walk generation process based upon loglinear topic model. They use this to explain some properties of word embeddings, including their use to solve analogies.

  7. Adaptive neuro fuzzy inference system - Wikipedia

    en.wikipedia.org/wiki/Adaptive_neuro_fuzzy...

    The first layer takes the input values and determines the membership functions belonging to them. It is commonly called fuzzification layer. It is commonly called fuzzification layer. The membership degrees of each function are computed by using the premise parameter set, namely {a,b,c}.

  8. Layer (deep learning) - Wikipedia

    en.wikipedia.org/wiki/Layer_(Deep_Learning)

    The Pooling layer [5] is used to reduce the size of data input. The Recurrent layer is used for text processing with a memory function. Similar to the Convolutional layer, the output of recurrent layers are usually fed into a fully-connected layer for further processing. See also: RNN model. [6] [7] [8] The Normalization layer adjusts the ...

  9. Category : Python (programming language) web frameworks

    en.wikipedia.org/wiki/Category:Python...

    This category lists web frameworks written in and/or designed for use with Python. Pages in category "Python (programming language) web frameworks" The following 25 pages are in this category, out of 25 total.