Artificial Intelligence: An overview | ||||
| The International Undergraduate Research Conference | ||||
| Volume 6, Issue 6, September 2022, Page 1-7 PDF (495.17 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/iugrc.2022.303092 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Ramez Yousri; Gehad Hany | ||||
| Egyptian Chinese University, Egypt. | ||||
| Abstract | ||||
| Intelligence has been, since the dawn of humanity, the driving factor for the development of civilization and humanity’s progress. In this survey paper, we give an overview of the field of Artificial Intelligence (AI) with its various subfields like Deep learning and neural networks. Artificial Intelligence (AI) isn’t only concerned with understanding intelligence but also building machines that can “think” or in other words building intelligent entities that can compute how to act effectively in novel situations. The term AI encompasses many fields, from general fields like learning, perception, intelligent decision making, etc to the specific like playing chess, Tetris, or performing image detection and analysis. This paper reviews the main methods and algorithms used in the field of AI starting with an overview of machine learning, supervised and unsupervised learning, concluding with deep learning and neural networks. It is sufficient to state that all machine learning algorithms are artificial intelligence approaches, yet not all AI methods qualify as machine learning algorithms. While deep learning is concerned with creating models (algorithms) that study data with multiple factors | ||||
| Keywords | ||||
| Intelligence; Artificial Intelligence; Supervised learning; Unsupervised learning; Deep learning; Neural Networks | ||||
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