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Natural language processing (NLP) is an interdisciplinary subfield of computer science and artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
e. Neuro-linguistic programming (NLP) is a pseudoscientific approach to communication, personal development and psychotherapy, that first appeared in Richard Bandler and John Grinder 's 1975 book The Structure of Magic I. NLP asserts that there is a connection between neurological processes, language and acquired behavioral patterns, and that ...
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.
Nonlinear programming. In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints are not linear equalities or the objective function is not a linear function. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective ...
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals, rather than relying on external labels provided by humans. In the context of neural networks, self-supervised learning aims to leverage inherent structures or relationships within the input ...
Representational systems (NLP) Representational systems (also abbreviated to VAKOG[1]) is a postulated model from neuro-linguistic programming, [2] a collection of models and methods regarding how the human mind processes and stores information. The central idea of this model is that experience is represented in the mind in sensorial terms, i.e ...
Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as a human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data to expected output values. [ 1 ]
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 ]