Deep learning has significantly increased in popularity in recent years, especially in domains that need substantial information. This technology is used in a wide range of areas, particularly in the field of biomedicine, where the limited availability of medical resources presents considerable difficulties. This work presents a new approach for categorizing skin conditions using advanced Machine Learning (ML) methods. We will conduct a thorough analysis that includes a detailed examination of datasets, procedures for preparing data, categorization models, and evaluation metrics. Our system implementation utilizes the Keras Deep Learning framework and Convolutional Neural Networks (CNNs) to classify skin disorders efficiently. We have incorporated sophisticated designs such as Inception-V4 and Long Short-Term Memory (LSTM) networks to improve performance. The impressive results demonstrate extraordinary outcomes with a remarkable test accuracy percentage of 99.61%.