This project aims to develop a prediction model for loan approval using logistic regression. The data for this project will be collected from a Kaggle public dataset and will include information on the loan applicant such as Credit_Score, income, loan_amount, and other relevant variables.
Goal: Usage of dataset to train a machine learning model that can accurately predict whether or not a loan application will be approved. In order to achieve this goal, various statistical techniques will be utilized.
Ultimately, the project aims to provide valuable insights into the factors that influence loan approval. This model will be built using Python & R and the necessary libraries such as pandas, scikit-learn, numpy, etc.
We would love to hear your feedback or any suggestions. Please feel free to open an issue or submit a pull request 👐