A Comprehensive Deep Dive into Machine Learning: Types, Techniques, and Unravelling its Impact on Diverse Domains

Abstract

This research aims to provide a comprehensive and in-depth review of the field of machine learning, focusing on its types and techniques, and clarifying the impact of this approach on many fields. Machine learning techniques are one of the most important pivotal tools that contribute to understanding and analyzing data more deeply and accurately. These techniques allow for improving efficiency and enhancing the learning ability of intelligent systems, making them essential in modern technological developments. The main objective of this research is to provide a classification that includes the types of machine learning and review the different techniques used in this field with the results of the impact of using these techniques as well as clarifying the benefits and disadvantages of these techniques while clarifying the impact of these techniques on different fields. The research is based on reviewing the strengths and weaknesses of these techniques and addressing the most important ways to deal with them. The research also includes studying the impact of machine learning on various fields, as well as the challenges and opportunities available to benefit from machine learning to obtain useful and comprehensive results on a global scale and discussing the future direction of machine learning techniques. This study, despite our entry into the crossroads of technological development, has demonstrated how deep learning techniques can be used in various fields to improve outcomes, highlight the importance of machine learning in enhancing intelligent technologies, and show how this learning can play a pivotal role in enhancing the learning and adaptive capabilities of intelligent systems and improving the performance of these systems to advance significantly in various fields.