Machine Learning and its impact on everyday life
Session
Computer Science and Communication Engineering
Description
This study focuses on Machine Learning technology and its use in everyday life. In this paper, we will analyze the historical development of Machine Learning technology, its key components, and its applications in daily life, particularly in the fields of healthcare, education, its role as a personal assistant and the implementation of recommendations and predictions in various applications. Furthermore, we will explore the need for Machine Learning in the business world and the risk associated with data usage in this context. Finally, we will examine the latest trends in Machine Learning development and the future possibilities for its use in various life domains. This analysis will be beneficial in understanding the functionality of Machine Learning in the background together with the risks and opportunities of Machine Learning in this rapidly evolving technological landscape.
Keywords:
Machine Learning, Technology Trends, Machine Learning Evolution, Recommendations of Machine Learning.
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-95-6
Location
UBT Lipjan, Kosovo
Start Date
28-10-2023 8:00 AM
End Date
29-10-2023 6:00 PM
DOI
10.33107/ubt-ic.2023.276
Recommended Citation
Ademi, Rina and Leka, Hizer, "Machine Learning and its impact on everyday life" (2023). UBT International Conference. 11.
https://knowledgecenter.ubt-uni.net/conference/IC/CS/11
Machine Learning and its impact on everyday life
UBT Lipjan, Kosovo
This study focuses on Machine Learning technology and its use in everyday life. In this paper, we will analyze the historical development of Machine Learning technology, its key components, and its applications in daily life, particularly in the fields of healthcare, education, its role as a personal assistant and the implementation of recommendations and predictions in various applications. Furthermore, we will explore the need for Machine Learning in the business world and the risk associated with data usage in this context. Finally, we will examine the latest trends in Machine Learning development and the future possibilities for its use in various life domains. This analysis will be beneficial in understanding the functionality of Machine Learning in the background together with the risks and opportunities of Machine Learning in this rapidly evolving technological landscape.