A brain tumor is caused by abnormal cell development within the brain and can be benign or malignant. Malignant tumors are particularly difficult to diagnose and treat, requiring significant resources, competent personnel, and cutting-edge technology. Early detection of brain cancers is critical for effective therapy, but existing manual approaches are invasive and risky. Medical imaging techniques such as magnetic resonance imaging (MRI) have proven critical for early detection, notwithstanding the difficulty that radiologists face. Misdiagnosis might occur due to a lack of trained professionals. In image classification tasks, artificial intelligence (AI) and computer vision have achieved human-level accuracy. In this chapter, we present AI algorithms for detecting brain tumors in brain MRI scans. For this, we use advanced convolutional neural networks and transfer learning. To diagnose abnormalities, we also use machine learning algorithms trained on embeddings resulting from deep feature extraction of MRI data. The chapter compares various deep learning models and strategies for automatic brain tumor detection.