A cancerous tumour in a woman's breast, Histopathology detects breast cancer. Histopathological images are a hotspot for medical study since they are difficult to judge manually. In addition to helping doctors identify and treat patients, this image classification can boost patient survival. This research addresses the merits and downsides of deep learning methods for histopathology imaging of breast cancer. The study's histopathology image classification and future directions are reviewed. Automatic histopathological image analysis often uses complete supervised learning where we can feed the labeled dataset to model for the classification. The research methods are frequentlytrust on feature extraction techniques tailored to specific challenges, such as texture, spatial, graph-based, and morphological features. Many deep learning models are also created for picture classification. There are various deep learning methods for classifying histopathology images
