To develop a machine learning model that can accurately predict loan approval for students in the education sector.
To identify key factors that influence loan approval decisions in educational institutions.
To optimize the loan approval process to increase efficiency and reduce human errors.
To improve financial management within educational institutions by leveraging machine learning techniques.
Collect and preprocess relevant data on loan applications and approval decisions from educational institutions.
Explore different machine learning algorithms and determine the most suitable model for loan approval prediction.
Build, train, and evaluate the machine learning model using the collected data.
Identify and analyze the key factors that affect loan approval decisions in the education sector.
Optimize the model to improve accuracy and efficiency in predicting loan approvals.
Present findings and recommendations based on the results of the project.
