Exploring the Depths: A Comprehensive Survey of Neural Networks and their Applications

This paper reviews the history and use of neural networks technology in great details. It starts by demonstrating the range of tasks neural networks can tackle, which are not limited to structural engineering or medical imaging. Then, it proceeds to outline the principles of artificial neural network models such as feedforward, recurrent and convolutional neural networks. The paper focuses on the training of neural networks and provides an account of the development of the backpropagation algorithm, optimization strategies, and regularization approaches. Moreover, a variety of case studies of neural networks applications are presented, for example, in climate modelling, natural language and speech recognition, computer vision and defect diagnosis techniques. In addition, the paper highlights the impact of the latest transformer models on self-supervised learning in natural language processing. The last part tackles ethical issues that are related to the use of neural networks such as fairness, bias and interpretability. All in all, this survey witnesses the growing importance of neural networks as a tool for enhancing the computational capabilities and addressing difficult problems.