Introduction to machine learning for making prediction easy and accurate

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.