Abstract
The definition of a brain tumor is the development of aberrant brain cells, some of which may progress to cancer. Magnetic Resonance Imaging (MRI) scans are the conventional technique for finding brain tumors. Applying Machine Learning (ML) and Deep Learning (DL)-based algorithms to efficiently identify the existence of brain tumors from Magnetic Resonance Imaging scans is a more effective and reliable technique. Both Machine Learning and Deep Learning algorithms were utilized in this paper, and their performance was examined. A thorough comparison between the two approaches was also given. It takes extremely little time to forecast a brain tumor when these algorithms are applied to Magnetic Resonance Imaging pictures, and the better accuracy makes it easier to treat patients. The radiologist can make speedy decisions thanks to these projections.