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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The use of different model parameters and different corpus sizes can greatly affect the quality of a word2vec model. Accuracy can be improved in a number of ways, including the choice of model architecture (CBOW or Skip-Gram), increasing the training data set, increasing the number of vector dimensions, and increasing the window size of words ...

  3. Gensim - Wikipedia

    en.wikipedia.org/wiki/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 collections using data streaming and ...

  4. Vector space model - Wikipedia

    en.wikipedia.org/wiki/Vector_space_model

    Candidate documents from the corpus can be retrieved and ranked using a variety of methods. Relevance rankings of documents in a keyword search can be calculated, using the assumptions of document similarities theory, by comparing the deviation of angles between each document vector and the original query vector where the query is represented as a vector with same dimension as the vectors that ...

  5. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  6. Latent semantic analysis - Wikipedia

    en.wikipedia.org/wiki/Latent_semantic_analysis

    The probabilistic model of LSA does not match observed data: LSA assumes that words and documents form a joint Gaussian model (ergodic hypothesis), while a Poisson distribution has been observed. Thus, a newer alternative is probabilistic latent semantic analysis, based on a multinomial model, which is reported to give better results than ...

  7. Infusion pump - Wikipedia

    en.wikipedia.org/wiki/Infusion_pump

    The user interface of pumps usually requests details on the type of infusion from the technician or nurse that sets them up: . Continuous infusion usually consists of small pulses of infusion, usually between 500 nanoliters and 10 milliliters, depending on the pump's design, with the rate of these pulses depending on the programmed infusion speed.

  8. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.

  9. Mathematical modelling of infectious diseases - Wikipedia

    en.wikipedia.org/wiki/Mathematical_modelling_of...

    If a model makes predictions that are out of line with observed results and the mathematics is correct, the initial assumptions must change to make the model useful. [ 13 ] Rectangular and stationary age distribution , i.e., everybody in the population lives to age L and then dies, and for each age (up to L ) there is the same number of people ...

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