Worldwide, breast cancer is the most common type of cancer in women and the second highest in terms of mortality rates.Diagnosis of breast cancer is performed when an abnormal lump is found (from self-examination or x-ray) or a tiny speck of calcium is seen (on an x-ray). After a suspicious lump is found, the doctor will conduct a diagnosis to determine whether it is cancerous and, if so, whether it has spread to other parts of the body.So using dataset and machine learning techniques. Using this we wish to classify the carcinogenic cells from the benign cells. This will help to reduce the load on the doctors as the machine will do the work for them. We will try to improve the accuracy as much as possible. Sick cells need to be located to find out how advanced the disease is and which grade should be assigned. This has to be done manually and is a time consuming process. Furthermore the decision depends on the expertise of the pathologist and his or her equipment. Therefore deep learning could be of great help to automatically detect and locate tumor tissue cells and to speed up the process.