Explore advanced methods for time series forecasting with XGBoost in this 22-minute video tutorial. Delve into techniques such as outlier removal, time series cross validation, and lag features. Learn how to implement these advanced strategies to enhance your forecasting models. Follow along with the provided Kaggle notebook to practice hands-on. Discover a bonus feature at the end of the tutorial to further improve your time series forecasting skills. Perfect for those who have already covered the basics and are looking to take their XGBoost forecasting abilities to the next level.
Time Series Forecasting with XGBoost - Advanced Methods
Overview
Syllabus
Start
Outline
Outlier Removal
Time Series Cross Validation
Lag Features
Training Cross Validation
Predicting the Future
Bonus!
Taught by
Rob Mulla
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