Information about Test

  1. Machine learning

    aimlexchange.com/search/wiki/page/Machine_learning

    Machine learning (ML) is the study of computer algorithms that improve automatically through experience. It is seen as a subset of artificial intelligence

  2. Active learning (machine learning)

    aimlexchange.com/search/wiki/page/Active_learning_%28machine_learning%29

    Active learning is a special case of machine learning in which a learning algorithm can interactively query a user (or some other information source) to

  3. Boosting (machine learning)

    aimlexchange.com/search/wiki/page/Boosting_%28machine_learning%29

    In machine learning, boosting is an ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine

  4. Deep learning

    aimlexchange.com/search/wiki/page/Deep_learning

    Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with

  5. List of datasets for machine-learning research

    aimlexchange.com/search/wiki/page/List_of_datasets_for_machine-learning_research

    for machine-learning research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major

  6. Automated machine learning

    aimlexchange.com/search/wiki/page/Automated_machine_learning

    Automated machine learning (AutoML) is the process of automating the process of applying machine learning to real-world problems. AutoML covers the complete

  7. Hyperparameter (machine learning)

    aimlexchange.com/search/wiki/page/Hyperparameter_%28machine_learning%29

    In machine learning, a hyperparameter is a parameter whose value is used to control the learning process. By contrast, the values of other parameters

  8. Supervised learning

    aimlexchange.com/search/wiki/page/Supervised_learning

    Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs. It infers

  9. Transformer (machine learning model)

    aimlexchange.com/search/wiki/page/Transformer_%28machine_learning_model%29

    The Transformer is a deep learning model introduced in 2017, used primarily in the field of natural language processing (NLP). Like recurrent neural networks

  10. Support vector machine

    aimlexchange.com/search/wiki/page/Support_vector_machine

    In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that

Contents