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A Comprehensive Overview of Neural Networks, Deep Learning and Machine Learning Applications in Engineering Fields

•   Mr. Saeed Hamidi ,  Birjand university ,   
•   Aboulfazl Yousefi ,  Birjand university ,   
•   Dr. Hashem Jahangir ,  Birjand university ,   

Major Topic: Structural Analysis Methods|روش های تحلیل سازه

Abstract

Machine learning is an enchanting realm of computer science that delves into the creation of enchanting algorithms and models that possess the mystical ability to automatically learn from the vast expanse of data. These wondrous algorithms possess the power to unravel hidden patterns, foretell impending outcomes, and conjure decisions with the guidance of input data. Behold, neural networks emerge as mesmerizing computational models that mirror the intricate design of the human nervous system. These ethereal networks are composed of captivating layers and interconnected computational units that dance in harmonious unity. Deep learning is a mesmerizing subset of machine learning that emerges as a captivating discipline that fixates on the utilization of neural networks adorned with an extravagant number of layers and units. These ethereal networks possess the otherworldly ability to extract profound wisdom from the complexities of data and the depths of intricate structures. They are summoned forth to fulfill tasks of great magnitude, such as the recognition of ethereal images, the translation of tongues, and the processing of the bountiful language of nature. Within this sacred tome, in this paper embarked on a comprehensive odyssey through the sacred principles of deep learning and machine learning. This paper unraveled the enigmatic concepts, and mystical methods, and manifested the enchanting applications that dwell within these realms. As the quest draws to a close, the current study embarked upon a profound reflection, gazing upon the strengths and weaknesses that grace these realms and the outcomes they bestow upon the seekers who dare to venture forth.

Keywords

Neural Network; Machine learning; Deep learning; Data Mining

• Deep learning and machine learning have had a significant impact on various industries and domains.
• Neural networks emerged in the 1950s and have since undergone advancements in hardware and algorithms.
• Deep learning has been successfully applied in fields such as medicine, object detection, facial recognition, and image classification.
• There are different architectures and methodologies for deep learning neural networks, including convolutional methods.
• The analysis and processing of multidimensional datasets require innovative algorithms to extract valuable information.
• Machine learning involves the construction of analytical models and tackles various tasks through the utilization of specific data.
• Federated learning, edge computing, and hardware architectures inspired by the human brain are areas of research in machine learning.
• Optimization algorithms, component pruning, and sparse networks are methods used to enhance the efficiency of neural networks.
• Supervised learning includes regression and classification tasks.