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Machine Learning and Pattern Recognition | | UPV

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30.10.2024 09:35
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Обучение

Описание

Título: Machine Learning and Pattern Recognition

Descripción: Four general definitions of Machine Learning (ML), from well-know machine
learners, are first provided as an approximation to define its main
objective. Siimilarly, then three general definitions of Pattern Recognition
(PR), by three renowned authors, are discussed. These discussions are followed
be an introduction of the main paradigm for ML/PR systems: the classification
paradigm. It is illustrated by a simple OCR example, which is also the used to
describe the conventional structure of a classifier and the two conventional
learning methods. Later, a few, outstanding application examples of ML/PR
systems are given, and the presentation ends by providing references to cited
authors.

The training objectives are: 1) To define machine learning and pattern recognition; 2) To interpret the classification paradigm and the conventional classifier structure; 3) To understand the conventional learning methods; and 4) To know some pattern recognition applications. Juan Císcar, A.; Civera Saiz, J.; Sanchis Navarro, JA. (2018). Machine Learning and Pattern Recognition. http://hdl.handle.net/10251/104577


Autor/a: Juan Ciscar Alfons



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#artificial intelligence #intelligent systems #machine learning #pattern recognition #1203 - Ciencias de la Computación

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