A Survey of Deep Learning and Machine Learning Techniques and Their Real-World Applications

Abstract

Recognition of images and voices, processing of natural languages, and even healthcare are just a few areas that have benefited greatly from the advent of machine learning and deep learning. Machine learning and deep learning are discussed in this article along with their methodologies and applications. We will go over their strengths and flaws and where they may go from here. Data privacy, ethical concerns, and the necessity for open decision-making are some of the problems we address while talking about these technologies. Two of the most ground-breaking developments in AI recently have been machine learning and deep learning. Their capacity to analyze massive information, provide forecasts, and deliver previously unattainable insights has led to their meteoric rise in popularity in recent years. Machine learning and deep learning will be defined, compared, and discussed in this article along with their uses and effects on different sectors. New opportunities for innovation are being unlocked by machine learning and deep learning, which are revolutionizing our interactions with technology. There are a number of sectors that have already felt the effects of these technologies, and they may yet have more revolutionary potential. The essay delves deeply into the fundamentals of deep learning and machine learning, outlining their distinctions, uses, and societal effects. This article seeks to provide light on the future possibilities and consequences of deep learning and machine learning by concentrating on recent literature and research in the field.