Personalised Skin Care Recommendation Using Machine Learning

Abstract

Acne is a common skin condition that can cause both physical and emotional distress for many individuals. Acne can be prevented and treated with skincare products, but choosing the right ones can be challenging. The use of inappropriate skincare products can even worsen the condition. To address this problem, we propose using machine learning to analyse various features of an individual’s skin quality and acne status and then recommend the most appropriate facial skincare products for that person. This approach takes into account the specific needs of each individual’s skin type and can help prevent the use of products that may exacerbate the condition. Several research papers regarding skin care product recommendation were reviewed and an appropriate solution to address this problem was concluded. You Only Look Once (YOLO) and Convolutional Neural Network (CNN) algorithms assist in determining the skin concern and recommending a skin care regimen. This system provides a precise idea of which product is best for our skin type. The suggestion for skincare products is based on different types of skin that people may have.  By using this approach, the final result is expected to have an accuracy score of over 97%.