The most frequent cancer in women globally is breast cancer, and effective treatment of the condition depends on early identification. Machine learning, a branch of artificial intelligence, has seen growing use in recent years in breast cancer detection and diagnosis using medical imaging. The use of machine learning algorithms in the cancer field can potentially improve the accuracy and efficiency of breast cancer detection. There are several machine learning techniques that have been applied in breast cancer detection, including supervised learning, deep learning, machine learning and unsupervised learning. The evaluation can be done using metrics such as sensitivity, specificity, accuracy, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. The algorithm learns to identify patterns and features in the images that are indicative of cancer.