Abstract:
Today's digital world includes IoT data, network security data, mobile data, business data, inf ormation technology, data health, etc. It is rich in data. Knowledge of artificial intelligence ( AI) and especially machine learning (ML) is required to intelligently look at this data using r obots and engage in data connectivity. There are many types of machine learning in this field, such as supervised learning, unsupervised learning, semi-supervised learning and additive learning. Data entry from the computer can be in the form of digital education or interaction with the environment. In this article, we provide a comprehen sive review of machine learning algorithms that can be used to increase the intelligence and c apabilities of the application. Therefore, the importance of this study highlights the ethical as pects of machine learning and their implications for cybersecurity systems, smart cities, medi cine, e-commerce, agriculture, etc. To explain its applications in various areas of the world.
