Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization

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Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization

This work aims to provide profound insights into neural networks and deep learning, focusing on their functioning, interpretability, and generalization capabilities. It explores fundamental aspects such as network architectures, activation functions, and learning algorithms, analyzing their theoreti...

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Bibliographic Details
Main Authors:	Usmani, Usman Ahmad, Usmani, Mohammed Umar
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2023
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/38934/ http://umpir.ump.edu.my/id/eprint/38934/1/Theoretical_Insights_into_Neural_Networks_and_Deep_Learning_Advancing_Understanding_Interpretability_and_Generalization.pdf http://umpir.ump.edu.my/id/eprint/38934/2/Theoretical%20Insights%20into%20Neural%20Networks%20and%20Deep%20Learning.pdf

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