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  2. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning models are often vulnerable to manipulation and/or evasion via adversarial machine learning. Researchers have demonstrated how backdoors can be placed undetectably into classifying (e.g., for categories "spam" and well-visible "not spam" of posts) machine learning models which are often developed and/or trained by third parties.

  3. 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.

  4. 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 a brain.

  5. 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 ...

  6. 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.

  7. Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Supervised_learning

    Supervised learning. Supervised learning ( SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. [1]

  8. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Further, specialized hardware and algorithm optimizations can be used for efficient processing of deep learning models. Deep learning revolution How deep learning is a subset of machine learning and how machine learning is a subset of artificial intelligence (AI) In the late 2000s, deep learning started to outperform other methods in machine ...

  9. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom , as a result of advances in deep neural networks .