Numerous studies in the biological sciences have been conducted as a result of the demand for innovative medical treatments and ongoing efforts to better understand the biological causes of diseases. Large datasets that contain a lot of text and images can lead to a lot of practical issues. The classification of this data requires the use of neural networks and other related architectures. Deep learning's potential for machine learning has made it more significant. The present endeavor aims to develop an approach for acute leukemia categorization using a deep learning technique. It demonstrates to be a potent supplementary clinical test for determining the severity of a patient's illness. GPU processing capability is used to develop a computerized recognition and categorization system for acute leukemia identification from peripheral blood pictures.