Objective:

Develop a machine learning model to predict mental health conditions of workers in tech industry.

Link for the dataset:

https://www.kaggle.com/datasets/ron2112/mental-health-data

Machine Learning Algorithms:

Employed four popular machine learning algorithms: Decision Tree, Logistic Regression,Random Forest and KNN.

Features Used for Prediction:

Model considers a variety of factors, including demographic information, workplace environment, and mental health symptoms and diagnoses.

Performance Metrics:

Evaluated model performance using multiple metrics:

Accuracy: Measure of overall correctness.

Precision: Proportion of true positive predictions among all positive predictions.

Recall: Proportion of true positive predictions among all actual positives.

F1 Score: Harmonic mean of precision and recall.

Results:

1)Logistic Regression

2)Decision Tree

3)Random Forest

Implications:

The project's findings have the potential to benefit organizations by identifying employees at risk of mental health conditions.

Allows organizations to provide the necessary support and resources to manage mental health effectively in the workplace.