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About Dataset
Skin Type Prediction Dataset 🧴✨
Overview
This dataset is designed for predicting skin types based on various factors such as age, gender, hydration level, oil level, sensitivity, humidity, and temperature. With 2,000 rows, it provides a diverse set of data points that can be used to develop machine learning models for skin type classification and personalized skincare recommendations.
Features
- Age: Age of the individual.
- Gender: Male or Female.
- Hydration_Level: Indicates the hydration level of the skin (Low, Medium, High).
- Oil_Level: Categorizes oil production levels (Low, Medium, High).
- Sensitivity: Indicates the skin's sensitivity (Low, Medium, High).
- Humidity: The humidity level at the time of observation.
- Temperature: The surrounding temperature.
- Skin_Type: The target variable, categorized as Dry, Oily, Normal, or Combination.
Applications
- Machine Learning & AI: Train predictive models to classify skin types.
- Skincare Personalization: Recommend suitable skincare products based on skin type.
- Data Analysis & Research: Analyze how environmental factors affect different skin types.
Usage
This dataset is ideal for data science projects, classification models, and exploratory data analysis. Whether you're a researcher, developer, or skincare enthusiast, this dataset provides a foundation for understanding skin characteristics and optimizing skincare recommendations.