vinit714/A-Recommendation-system-for-Facial-Skin-Care-using-Machine-Learning-Models
Transforming skincare recommendations: our hybrid system combines KNN, CNN, and EfficientNet B0 for personalized advice. Published in IEEE, with 80% validation accuracy and 87.10% training accuracy.
This system helps you find the right facial skincare products by analyzing your skin. You input details like your skin tone, type (oily, dry, standard), and acne severity, and it recommends suitable products. It's designed for anyone looking for personalized advice on skincare to address their specific concerns.
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Use this if you want an automated, personalized recommendation for facial skincare products based on your unique skin characteristics and concerns.
Not ideal if you prefer generic skincare advice or are not comfortable providing details about your skin for analysis.
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Apr 29, 2024
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