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Predicting Credit Card Approvals

Build a machine learning model to predict if a credit card application will get approved.

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12 Tasks1,500 XP19,144 Learners

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Project Description

Commercial banks receive a lot of applications for credit cards. Many of them get rejected for many reasons, like high loan balances, low income levels, or too many inquiries on an individual's credit report, for example. Manually analyzing these applications is mundane, error-prone, and time-consuming (and time is money!). Luckily, this task can be automated with the power of machine learning and pretty much every commercial bank does so nowadays. In this project, you will build an automatic credit card approval predictor using machine learning techniques, just like the real banks do. The dataset used in this project is the [Credit Card Approval dataset]( from the UCI Machine Learning Repository.

Project Tasks

  1. 1
    Credit card applications
  2. 2
    Inspecting the applications
  3. 3
    Handling the missing values (part i)
  4. 4
    Handling the missing values (part ii)
  5. 5
    Handling the missing values (part iii)
  6. 6
    Preprocessing the data (part i)
  7. 7
    Splitting the dataset into train and test sets
  8. 8
    Preprocessing the data (part ii)
  9. 9
    Fitting a logistic regression model to the train set
  10. 10
    Making predictions and evaluating performance
  11. 11
    Grid searching and making the model perform better
  12. 12
    Finding the best performing model


Python Python


Data ManipulationMachine LearningImporting & Cleaning DataApplied Finance
Sayak  Paul Headshot

Sayak Paul

Deep Learning Associate at PyImageSearch

Sayak is currently a Deep Learning Associate at PyImageSearch. His subject of interest lies in the area of self-supervised visual representation learning. He enjoys applying deep learning to solve real-world problems. Off the work Sayak likes to blog about different topics in machine learning and speak at developer meetups. Check out his site to find out more about him and how to contact him.
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