To analyze the factors contributing to customer churn in tech companies.
To explore and select appropriate machine learning algorithms for predicting customer churn.
To develop a predictive model using the selected algorithms and evaluate its accuracy and performance.
Conduct a literature review on customer churn in tech companies and the use of machine learning for prediction.
Collect and preprocess relevant data on customer behavior and churn from a tech company.
Select and apply appropriate machine learning algorithms for predicting customer churn, such as logistic regression, decision trees, or random forests.
Train and validate the predictive model using the collected data.
Evaluate the model's performance using metrics such as accuracy, precision, recall, and F1 score.
Write a research report documenting the methodology, results, and conclusions of the project.
