Sleep Time Prediction

Title: Sleep Time Prediction Dataset

Description:
This dataset is designed for machine learning models to predict sleep duration based on daily lifestyle parameters. The data includes features like workout time, reading time, phone usage time, work hours, caffeine intake, and relaxation time, with sleep time as the target variable.

Context:
The dataset was generated based on a mathematical equation simulating how lifestyle factors influence sleep duration. It includes outliers to make models robust to noisy real-world data.

Source:
Generated synthetically using a Python script.
NOTE : This dataset has been synthetically generated and does not contain any real-world data. The features and target variable are independent and do not exhibit any meaningful relationships.
Inspiration:

• Explore the impact of lifestyle choices on sleep duration.
• Train regression models and evaluate their performance.
• Fine-tune sleep prediction algorithms for health and wellness applications.