This is my collection of Machine Learning mini-projects as I'm learning ML. I hope you will find them useful as you embark on the same journey.
Recommended order for exploring these projects is as follows:
- First XGBoost Model with scikit-learn
- Data Preparation for Gradient Boosting with XGBoost
- Save Gradient Boosting Models with XGBoost
- Evaluate Gradient Boosting Models with XGBoost
- Visualize Gradient Boosting Decision Trees With XGBoost
- Feature Importance and Feature Selection With XGBoost
- Avoid Overfitting by Early Stopping With XGBoost
- Tune Multithreading Support for XGBoost
- Tune the Number and Size of Decision Trees with XGBoost
- Tune Learning Rate for Gradient Boosting with XGBoost
- Stochastic Gradient Boosting with XGBoost