ARTIFICIAL NEURAL NETWORK ARCHITECTURES FOR MODERN MACHINE LEARNING SYSTEMS
Keywords:
Keywords: artificial intelligence, neural networks, machine learning, perceptron, deep learning, algorithms, Frank Rosenblatt (F. Rosenblatt), E.Xant, Donald Hebb (D.Hebb), John von Neumann, Chen, Van Gerven, Liu.Abstract
Abstract: This paper provides a comprehensive analysis of artificial neural network (ANN) structures and their application in machine learning. The study explores the architecture, working principles, and learning mechanisms of neural networks. In addition, the historical development and modern applications of ANN in various fields are discussed. Special attention is given to their ability to model complex systems and process large datasets efficiently. The advantages and limitations of neural networks are also analyzed.
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