#First Personal Project - Sleep Quality Prediction

Demo

Here’s a preview of the Streamlit web app interface.

This is my first personal project aimed at building a full machine learning pipeline from scratch to deployment.

Project Overview

This project explores how smartphone usage patterns (for example screen time, app usage, notifications, sound environment...) before bedtime can affect sleep quality.

The goal is to create an AI model that predicts sleep quality and gives predictions based on real-world or simulated smartphone data.

Objectives

• Collect and preprocess sleep-related smartphone data
• Perform EDA i.e. exploratory data analysis
• Build and evaluate ML models
• Visualize key patterns and trends
• Deploy a working prototype (web app -> Streamlit)

Key Skills Practiced

• Data collection from real-world sources
• Feature engineering & time series analysis
• ML model training & evaluation
• Data visualization
• Model deployment (Streamlit)
• Version control and documentation

Status

• Project definition
• Data collection plan
• Initial dataset exploration
• Model training & evaluation
• Deployment setup

--28/06/2025