Part 3: Creating the Project Workspace & Libraries

3. Creating the Workspace

Create a folder named credit_card_project on your computer. Inside, organize your folders and empty files exactly like this:

credit_card_project/
├── data/
│   ├── application_record.csv
│   └── credit_record.csv
├── models/
│   └── card_model.joblib
├── templates/
│   └── index.html
├── static/
│   ├── style.css
│   └── script.js
├── notebook.ipynb
└── app.py

[!IMPORTANT] Beginner Rule: Whenever you write or paste code into any file in VS Code, remember to press Ctrl + S (Windows) or Cmd + S (macOS) to save your changes. If you do not save, the file remains empty and your code will not run!

3.1 Installing Required Libraries

Open your terminal inside your project folder and run the following installation command:

pip install numpy pandas matplotlib seaborn scikit-learn xgboost joblib flask

We install these key libraries:

• pandas: Loads, merges, and cleans our tabular CSV data.
• numpy: Handles mathematical logic on numerical matrix arrays.
• matplotlib & seaborn: Generates statistical charts and plots.
• scikit-learn: Houses our classifiers, data splitters, and validation metrics.
• xgboost: Builds our gradient boosted decision tree classifier.
• joblib: Saves our trained model weights into a portable file.
• flask: Runs our lightweight local backend application server.