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  2. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  3. Mamba (deep learning architecture) - Wikipedia

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

    Mamba [a] is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University to address some limitations of transformer models , especially in processing long sequences.

  4. BLOOM (language model) - Wikipedia

    en.wikipedia.org/wiki/BLOOM_(language_model)

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]

  5. Spark NLP - Wikipedia

    en.wikipedia.org/wiki/Spark_NLP

    Spark NLP for Healthcare is a commercial extension of Spark NLP for clinical and biomedical text mining. [10] It provides healthcare-specific annotators, pipelines, models, and embeddings for clinical entity recognition, clinical entity linking, entity normalization, assertion status detection, de-identification, relation extraction, and spell checking and correction.

  6. Random forest - Wikipedia

    en.wikipedia.org/wiki/Random_forest

    Decision trees are a popular method for various machine learning tasks. Tree learning is almost "an off-the-shelf procedure for data mining", say Hastie et al., "because it is invariant under scaling and various other transformations of feature values, is robust to inclusion of irrelevant features, and produces inspectable models.

  7. Feature (machine learning) - Wikipedia

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

    In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects, since such representations facilitate processing and statistical analysis. When representing images, the feature values ...

  8. Core Python Programming - Wikipedia

    en.wikipedia.org/wiki/Core_Python_Programming

    Core Python Programming is a textbook on the Python programming language, written by Wesley J. Chun. The first edition of the book was released on December 14, 2000. [1] The second edition was released several years later on September 18, 2006. [2] Core Python Programming is mainly targeted at higher education students and IT professionals. [3]

  9. Stop word - Wikipedia

    en.wikipedia.org/wiki/Stop_word

    Other search engines remove some of the most common words—including lexical words, such as "want"—from a query in order to improve performance. [7] In recent years the SEO best practices around stop words have evolved along with the fields of machine learning and natural language processing. In February 2021, John Mueller, Webmaster Trends ...