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Breast cancer is a very devastating type of cancer that typically develops in breast cells and in the past few decades, the incidence rate of breast cancer has risen steadily. The diagnosis mostly depends on the radiologists’ experience, questionable diagnoses are common, and there are worries about lawsuits due to incorrect diagnoses or missed lesions. Therefore, developing deep learning models for breast cancer identification is urgently needed, despite substantial advancements in the treatment of primary breast cancer during the past ten years. In Deep Learning, the convolutional neural network can be a useful technique for classification problems.In this study, some of the Transfer learning models are applied, which are pre-trained models that are trained on huge datasets such as the ImageNet dataset, which contains about 1.2 million images. However, these models are VGG16 VGG19 Mobilenet V2, and it …