enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Vector space model - Wikipedia

    en.wikipedia.org/wiki/Vector_space_model

    Vector space model. Vector space model or term vector model is an algebraic model for representing text documents (or more generally, items) as vectors such that the distance between vectors represents the relevance between the documents. It is used in information filtering, information retrieval, indexing and relevancy rankings.

  3. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] [18] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  4. BERT (language model) - Wikipedia

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

    Apache 2.0. Website. arxiv .org /abs /1810 .04805. Bidirectional Encoder Representations from Transformers ( BERT) is a language model introduced in October 2018 by researchers at Google. [ 1][ 2] It learned by self-supervised learning to represent text as a sequence of vectors. It had the transformer encoder architecture.

  5. Transformer (deep learning architecture) - Wikipedia

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

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  6. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    v. t. e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect ...

  7. Vector Institute (Canada) - Wikipedia

    en.wikipedia.org/wiki/Vector_Institute_(Canada)

    Research in machine learning. Headquarters. Toronto, Ontario, Canada. Employees. 714 [ 1] Website. www .vectorinstitute .ai. The Vector Institute is a private, non-profit artificial intelligence research institute in Toronto focusing primarily on machine learning and deep learning research. As of 2023, it consists of 143 faculty members and ...

  8. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    Foundation model. A foundation model, also known as large AI model, is a machine learning or deep learning model that is trained on broad data such that it can be applied across a wide range of use cases. [ 1] Foundation models have transformed artificial intelligence (AI), powering prominent generative AI applications like ChatGPT. [ 1]

  9. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    t. e. The scale-invariant feature transform ( SIFT) is a computer vision algorithm to detect, describe, and match local features in images, invented by David Lowe in 1999. [ 1] Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, individual identification of ...