This notebook is ispired by the AIX360 HELOC Credit Approval Tutorial, which shows different explainability methods for a credit approval process. Here XGBoost is used for classification, achieving better accuracy than most of the models used in that notebook. Then, feature importance methods are shown, to be compared with the Data Scientist exp…

In this prototype, credit card approval data was analysed and a machine learning model was created to forecast the approval of credit card requests.

A Django-based Credit Approval System that intelligently determines loan eligibility and offers real-time insights based on past loan data and customer profiles using PostgreSQL.

Classified and clustered bank clients with respect to their user profile and decided if they should get credit. KNN & KMeans algorithms, K-Fold developed in C without libraries.

From Philosophy to Interfaces: an Explanatory Method and a Tool Inspired by Achinstein’s Theory of Explanation

Exploratory Data Analysis about Credit Approval dataset

Credit Approval System: SVM Model (Built from scratch and compared against python sklearn fn)

Django-based REST API for automated credit approval and loan management with PostgreSQL, Redis, Celery, and Docker. Features credit score calculation, loan eligibility assessment, interest rate correction, and comprehensive API documentation with Swagger/OpenAPI integration.

Classifying credit applicants with 9 different ML models