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This study explored the potential of machine learning to improve the accuracy of skin cancer diagnosis. The decision tree algorithm emerged as the most effective, achieving an accuracy rate of 83%. Introducing deep learning, specifically a convolutional neural network (CNN), significantly boosted accuracy to nearly 94%. The research team achieved an accuracy rate of nearly 94% after just six training cycles.