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  2. Multimodal learning - Wikipedia

    en.wikipedia.org/wiki/Multimodal_learning

    Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...

  3. Multimodal sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Multimodal_sentiment_analysis

    Multimodal sentiment analysis also plays an important role in the advancement of virtual assistants through the application of natural language processing (NLP) and machine learning techniques. [5] In the healthcare domain, multimodal sentiment analysis can be utilized to detect certain medical conditions such as stress, anxiety, or depression. [8]

  4. Normalization (machine learning) - Wikipedia

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

    In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization and activation normalization . Data normalization (or feature scaling ) includes methods that rescale input data so that the features have the same range, mean, variance, or other ...

  5. ROUGE (metric) - Wikipedia

    en.wikipedia.org/wiki/ROUGE_(metric)

    ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, [1] is a set of metrics and a software package used for evaluating automatic summarization and machine translation software in natural language processing. The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced ...

  6. Natural Language Toolkit - Wikipedia

    en.wikipedia.org/wiki/Natural_Language_Toolkit

    The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. [4]

  7. Outline of natural language processing - Wikipedia

    en.wikipedia.org/wiki/Outline_of_natural...

    Machine learning – subfield of computer science that examines pattern recognition and computational learning theory in artificial intelligence. There are three broad approaches to machine learning. Supervised learning occurs when the machine is given example inputs and outputs by a teacher so that it can learn a rule that maps inputs to outputs.

  8. Methods of neuro-linguistic programming - Wikipedia

    en.wikipedia.org/wiki/Methods_of_neuro...

    The methods of neuro-linguistic programming are the specific techniques used to perform and teach neuro-linguistic programming, [1] [2] which teaches that people are only able to directly perceive a small part of the world using their conscious awareness, and that this view of the world is filtered by experience, beliefs, values, assumptions, and biological sensory systems.

  9. Calibration (statistics) - Wikipedia

    en.wikipedia.org/wiki/Calibration_(statistics)

    There are two main uses of the term calibration in statistics that denote special types of statistical inference problems. Calibration can mean a reverse process to regression, where instead of a future dependent variable being predicted from known explanatory variables, a known observation of the dependent variables is used to predict a corresponding explanatory variable; [1]