Alam, Md. AshrafulImamuzzaman, A.S.M.Sakline, Redwan IslamJunaed, Sayed RafiHossain, Mohammad IqbalDas, Dipto2021-10-112021-10-1120212021-06ID 20141034ID 16201013ID 17101064ID 17101279ID 17101135http://hdl.handle.net/10361/15203Cataloged from PDF version of thesis.Includes bibliographical references (page 38-39).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.A brain tumor is a collection of abnormal cells growth in brain. It is a neurological disease which causes great damage and affects other healthy cells of brain. It can be cancerous or non-cancerous. Nowadays, people are more concern about their health issues. So, in this thesis paper we will design and implement an efficient machine learning approach to detect brain tumor from image data. Moreover, the proposed model approaches VGG16 and ResNet50 architectural model of Convolutional Neu ral Network (CNN). Through this model a neurosurgeon can easily detect the brain tumor of a patient with more efficiency. Our proposed model uses MRI images, and we also make a comparison between the two architectures of CNN.39 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.CNNVGG16ResNet50Brain TumorBrain TumorThesis