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DepressionPrediction-EDA-5ML-Models

Goal:

This project aims to build an AI model to predict whether an individual is experiencing depression based on various psychological, lifestyle, and demographic factors. Depression is a serious mental health condition that affects mood, thinking, and daily activities. Early detection and intervention are crucial in managing depression and improving mental well-being.

Project Overview:

Dataset:

We will use the Depression Professional Dataset from Kaggle, which contains various attributes related to mental health, lifestyle habits, and work-related stress.

Problem Type:

This is a binary classification problem where the goal is to predict whether a person is suffering from depression (Yes or No).

Features:

Demographic factors (e.g., Age, Gender)

Lifestyle habits (e.g., Sleep Duration, Dietary Habits)

Work-related stress (e.g., Work Pressure, Financial Stress)

Mental health history (e.g., Family History of Mental Illness)

Target Variable: "Depression" (Yes/No), which serves as an indicator of severe depression.

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This project aims to build an AI model to predict whether an individual is experiencing depression based on various psychological, lifestyle, and demographic factors.

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