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  2. IBM Watson - Wikipedia

    en.wikipedia.org/wiki/IBM_Watson

    The high-level architecture of IBM's DeepQA used in Watson [9]. Watson was created as a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering.

  3. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    t. e. Machine learning ( ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. [ 1] Recently, artificial neural networks have been able to surpass many previous approaches ...

  4. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Machine learningand data mining. These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning ), computer hardware, and, less ...

  5. IBM SkillsBuild - Wikipedia

    en.wikipedia.org/wiki/IBM_SkillsBuild

    IBM SkillsBuild. IBM SkillsBuild is a free education program focused on underrepresented communities in tech, that helps adult learners, and high school and university students and faculty, develop valuable new skills and access career opportunities. The program includes an online platform that is complemented by customized practical learning ...

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier.. For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model.

  7. Adversarial machine learning - Wikipedia

    en.wikipedia.org/wiki/Adversarial_machine_learning

    Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. [1] A survey from May 2020 exposes the fact that practitioners report a dire need for better protecting machine learning systems in industrial applications. [2]

  8. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    Cross-industry standard process for data mining. The Cross-industry standard process for data mining, known as CRISP-DM, [1] is an open standard process model that describes common approaches used by data mining experts. It is the most widely-used analytics model. [2]

  9. Active learning (machine learning) - Wikipedia

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

    e. Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

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