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Skin care is a vital component of one's health and well-being, and there are many products on the market that report different skin problems. People's methods for skin issues have changed dramatically as a result of technological revolutions in the skin care industry and artificial intelligence (AI). The traditional approach of navigating multiple brand websites and overwhelming product choices has prompted the need for a more streamlined and intelligent solution. The AI-driven web application system is proposed to suggest appropriate skin care items depending on a particular skin type. It is an innovative system that brings product recommendations from several brands and websites, as well as cross-platform price comparisons, together in a single, customized area. It also provides a link to the particular platform so that customers may purchase products based on the quality and quantity of products. By using deep learning, which uses convolutional neural networks (CNNs) to understand complex patterns within skin data, users provide the system with an image along with additional information about their skin type, worries, and preferences, and help the system understand and recover appropriate data. The proposed system verifies user knowledge before and after system use, while experts examine rules and designs. By analyzing this data, the deep learning algorithm is able to recognize different skin outlines and certain disorders such as pigmentation, age, dryness, sensitivity, or acne. Also, a trained dataset is used to check for the training and validation accuracy of the system.
Hanchinal et al. (Fri,) studied this question.