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In this paper we use TDA mapper alongside with deep convolutional neural networks in the classification of 7 major skin diseases. First we apply kepler mapper with neural network as one of its
filter steps to classify the dataset HAM10000. Mapper visualizes the classification result by a simplicial complex, where neural network can not do this alone, but as a filter step neural network helps
to classify data better. Furthermore we apply TDA mapper and persistent homology to understand
the weights of layers of mobilenet network in different training epochs of HAM10000. Also we use
persistent diagrams to visualize the results of analysis of layers of mobilenet network.