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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    doc2vec, generates distributed representations of variable-length pieces of texts, such as sentences, paragraphs, or entire documents. [14] [15] doc2vec has been implemented in the C, Python and Java/Scala tools (see below), with the Java and Python versions also supporting inference of document embeddings on new, unseen documents.

  3. Quoc V. Le - Wikipedia

    en.wikipedia.org/wiki/Quoc_V._Le

    Quoc V. Le. Lê Viết Quốc (born 1982), [1] or in romanized form Quoc Viet Le, is a Vietnamese-American computer scientist and a machine learning pioneer at Google Brain, which he established with others from Google. He co-invented the doc2vec [2] and seq2seq [3] models in natural language processing. Le also initiated and lead the AutoML ...

  4. Gensim - Wikipedia

    en.wikipedia.org/wiki/Gensim

    Website. radimrehurek.com /gensim /. Gensim is an open-source library for unsupervised topic modeling, document indexing, retrieval by similarity, and other natural language processing functionalities, using modern statistical machine learning. Gensim is implemented in Python and Cython for performance. Gensim is designed to handle large text ...

  5. Deeplearning4j - Wikipedia

    en.wikipedia.org/wiki/Deeplearning4j

    t. e. Eclipse Deeplearning4j is a programming library written in Java for the Java virtual machine (JVM). [2][3] It is a framework with wide support for deep learning algorithms. [4] Deeplearning4j includes implementations of the restricted Boltzmann machine, deep belief net, deep autoencoder, stacked denoising autoencoder and recursive neural ...

  6. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    Diagram of the feature learning paradigm in ML for application to downstream tasks, which can be applied to either raw data such as images or text, or to an initial set of features of the data. Feature learning is intended to result in faster training or better performance in task-specific settings than if the data was input directly (compare ...

  7. Entity linking - Wikipedia

    en.wikipedia.org/wiki/Entity_linking

    Entity linking. In natural language processing, Entity Linking, also referred to as named-entity disambiguation (NED), named-entity recognition and disambiguation (NERD) or named-entity normalization (NEN) [1] is the task of assigning a unique identity to entities (such as famous individuals, locations, or companies) mentioned in text.