The application of machine learning in computing has become one of the most significant developments in modern technology. This study examines a range of use cases from various sectors, including healthcare, finance and transport, which demonstrate how machine learning can improve the efficiency, accuracy and capabilities of computer systems. Through case study analysis, it is shown that machine learning is capable of automating complex tasks and providing deep insights. However, the implementation of this technology also faces a number of challenges, such as the need for high-quality data, model interpretability issues, and high computational costs. Furthermore, there are ethical and legal issues to be considered, especially in relation to privacy and potential bias in the models. This research highlights the importance of a careful approach and appropriate strategies to overcome these barriers, in order to fully utilise the potential of machine learning while minimising the risks involved.
Copyrights © 2024