Applications of Machine Learning (Vol. II)

Abstract

The world has been dominated by Artificial Intelligence (AI), which has permeated every aspect of personal and professional life. Practical applications of AI abound, including intelligent healthcare applications, autonomous vehicles, and smart home devices, among many others. These applications have significantly altered our everyday lives. The capacity of computers to analyze and learn from data, acquire knowledge through experience, and forecast future outcomes has the potential to facilitate a vast array of challenges presently confronting society. Both machine learning and deep learning-based methodologies are classified as AI. Machine-learning-based methodologies prioritize the development of individualized solutions that have practical applications. The feature engineering process necessitates human intervention, whereas the algorithm discerns data across various classes or categories. Deep learning approaches offer a more comprehensive resolution by utilizing neural networks, which constitute the foundation of each deep learning model. In particular, an artificial neural network replicates the human brain’s functionality, enabling it to discern significant patterns from data without requiring manual feature design.