Build a Credit Scoring Model with Python | FinTech ML Project for Beginners

📘 Build a Credit Scoring Model with Python – A FinTech ML Labs Tutorial
This comprehensive, hands-on tutorial guides you through building a credit scoring model using Python, Pandas, and scikit-learn. You'll learn how to prepare and preprocess real-world loan data, engineer impactful features, and implement three essential machine learning algorithms:

- Logistic Regression

- Decision Tree Classifier

- Random Forest Classifier

We will also cover key model evaluation techniques—including precision, recall, F1-score, and accuracy to assess model performance and understand business impact.

🔍 What You Will Learn:
✅ Credit risk modeling fundamentals
✅ Binary classification using Logistic Regression
✅ Effective feature engineering & scaling techniques
✅ Comparing model performance using key metrics
✅ Practical, job-ready skills for fintech and data science careers

🎯 This tutorial is part of our FinTech ML Labs series, where we help you build real-world machine learning projects for finance and lending. Perfect for anyone looking to break into fintech or level up their ML portfolio.

🔗 GitHub Code & Dataset: https://github.com/epythonlab2/fintech-ml-labs
📺 Build FinTech ML Projects with Python (Intro Episode) – https://youtu.be/dy87uyYQWrg

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Видео Build a Credit Scoring Model with Python | FinTech ML Project for Beginners канала Epython Lab