Currently, many studies are being conducted to classify skin diseases at early stages and several solutions are being proposed. In particular, classification of skin diseases using medical images using intelligent systems is one of the best solutions proposed by researchers. In this research work, the methods, models and algorithms proposed by scientists for automatic classification of skin diseases based on computer-aided machine learning (ML) and deep learning (DL) algorithms were analyzed. Also, pre-processing methods for medical images were studied for the fast and accurate operation of ML and DL models. As a result of the analysis, comparative tables of previous and current research results and the models proposed in them were developed for further research work. The main goal of the study is to fill the research gap in the application of ML and DL models in skin disease classification, which will help researchers to find better solutions, to find out the current difficulties in classification and recent achievements.