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  2. Navy Marine Corps Intranet - Wikipedia

    en.wikipedia.org/wiki/Navy_Marine_Corps_Intranet

    Navy Marine Corps Intranet. The Navy/Marine Corps Intranet ( NMCI) is a United States Department of the Navy program which was designed to provide the vast majority of information technology services for the entire Department, including the United States Navy and Marine Corps .

  3. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).

  4. 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.

  5. Transformer (deep learning architecture) - Wikipedia

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

    As the model had difficulties converging, it was suggested that the learning rate should be linearly scaled up from 0 to maximal value for the first part of the training (i.e. 2% of the total number of training steps). The intent of the transformer model is to take a seq2seq model and remove its recurrent neural networks, but preserve its ...

  6. Timeline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Timeline_of_machine_learning

    1950s. Pioneering machine learning research is conducted using simple algorithms. 1960s. Bayesian methods are introduced for probabilistic inference in machine learning. [1] 1970s. ' AI winter ' caused by pessimism about machine learning effectiveness. 1980s.

  7. Convolutional neural network - Wikipedia

    en.wikipedia.org/wiki/Convolutional_neural_network

    Convolutional neural network ( CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections.

  8. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    A foundation model is a machine learning or deep learning model that is trained on broad data such that it can be applied across a wide range of use cases. [1] Foundation models have transformed artificial intelligence (AI), powering prominent generative AI applications like ChatGPT. [1] The Stanford Institute for Human-Centered Artificial ...

  9. Boosting (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Boosting_(machine_learning)

    Machine learningand data mining. In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, variance. [1] It is used in supervised learning and a family of machine learning algorithms that convert weak learners to strong ones. [2]

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