Name: Mathematics and Its Applications in Science and Engineering (en Inglés)
SKU: 57883744
Price: 102.61 USD
Availability: InStock
Author: Dios, Araceli Queiruga ; Santos, Maria Jesus ; Yilmaz, Fatih

portada Mathematics and Its Applications in Science and Engineering (en Inglés)

Mathematics and Its Applications in Science and Engineering (en Inglés)

Formato

Libro Físico

Editorial

Mdpi AG

Autor

Dios, Araceli Queiruga ; Santos, Maria Jesus ; Yilmaz, Fatih

Idioma

Inglés

N° páginas

392

Encuadernación

Tapa Dura

Dimensiones

24.4x17x3 cm

Peso

1.04 kg.

ISBN13

9783036555812

Categorías

Ciencias de la computación

Mathematics and Its Applications in Science and Engineering (en Inglés)

Dios, Araceli Queiruga ; Santos, Maria Jesus ; Yilmaz, Fatih (Autor) · Mdpi AG · Tapa Dura

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Reseña del libro "Mathematics and Its Applications in Science and Engineering (en Inglés)"

Natural language processing (NLP) is one of the most important technologies in use today, especially due to the large and growing amount of online text, which needs to be understood in order to fully ascertain its enormous value. During the last decade, the application of machine learning techniques has led to achievement of higher accuracy in many types of NLP applications. Although numerous machine learning models have been developed for NLP applications, deep learning approaches have recently achieved remarkable results across many NLP tasks. The present book contains all the articles accepted and published in the Special Issue "Natural Language Processing (NLP) and Machine Learning (ML)-Theory and Applications" of the MDPI journal Mathematics. A large range of research topics of NLP have been touched upon within this Special Issue, showcasing the diversity and dynamics of this perpetually evolving field, which is providing one of the most important technologies in use today. This Special Issue has provided a platform for researchers to present their novel work in the domain of NLP and its applications, with a focus on applications of machine learning and deep learning in this field. We hope that this will help to foster future research in NLP and all its related