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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Costa, C. (2024). Neural Networks: A Comprehensive Overview of Their History, Development, and Future in AI. OAE – Organizational Architect and Engineer Journal. Volume 6 (Issue 1)
Exportar Referência (IEEE) 
C. M. Costa,  "Neural Networks: A Comprehensive Overview of Their History, Development, and Future in AI", in OAE – Organizational Architect and Engineer Journal, vol. Volume 6, no. Issue 1, 2024
Exportar BibTeX 
@null{costa2024_1782842570183,
	year = "2024"
}
Exportar RIS 
TY  - GEN
TI  - Neural Networks: A Comprehensive Overview of Their History, Development, and Future in AI
T2  - OAE – Organizational Architect and Engineer Journal
VL  - Volume 6
AU  - Costa, C.
PY  - 2024
SN  - 2182-648X
DO  - 10.21428/b3658bca.13fccc0e
AB  - Neural networks, inspired by the functioning of the human brain, are a cornerstone of modern artificial intelligence (AI) research. This document traces the history, foundational concepts, types, and key applications of neural networks. Beginning with the pioneering work of McCulloch and Pitts, it outlines the significant developments that have shaped neural network models, from the Perceptron to advanced Deep Learning architectures like Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs). It also discusses essential neural network training techniques, including backpropagation, optimization strategies, and the role of hyperparameter tuning. Additionally, it contrasts Machine Learning and Deep Learning, highlighting their respective roles and computational requirements. Finally, the document introduces popular neural network frameworks such as TensorFlow and Keras, enabling the practical implementation of these models.
ER  -