Скачать или смотреть Complete Machine Learning Project: Python Credit Risk Model (XGBoost, RF)

Build a complete machine learning project in Python! In this 7-minute tutorial, we build a real-world credit risk model from start to finish in Google Colab.

We take a raw CSV file and walk through every step of a data science project:

Loading and exploring data with Pandas.

Analyzing our target variable and discovering a critical imbalanced data problem.

Preprocessing our data using Train-Test Split and StandardScaler.

Training FOUR powerful models: Logistic Regression, Random Forest, XGBoost, and LightGBM.

Evaluating our models using a Confusion Matrix and Classification Report to understand why accuracy isn't the most important metric!

By the end, you'll see which model performs best and understand how to handle common data science challenges like imbalanced classes.