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Time Series Forecasting with XGBoost - Advanced Methods

This video is a continuation of the previous video on the topic where we cover time series forecasting with xgboost. In this video we cover more advanced methods such as outlier removal, time series cross validation, lag features, and a bonus feature! Check out part 1 here:    • Time Series Forecasting with XGBoost ...   The notebook used in this video here: https://www.kaggle.com/code/robikscub... Timeline: 00:00 Start 01:05 Outline 02:20 Outlier Removal 04:25 Time Series Cross Validation 10:15 Lag Features 13:15 Training Cross Validation 14:52 Predicting the Future 20:09 Bonus! Follow me on twitch for live coding streams:   / medallionstallion_   My other videos: Speed Up Your Pandas Code:    • Make Your Pandas Code Lightning Fast   Speed up Pandas Code:    • Make Your Pandas Code Lightning Fast   Intro to Pandas video:    • A Gentle Introduction to Pandas Data ...   Exploratory Data Analysis Video:    • Exploratory Data Analysis with Pandas...   Working with Audio data in Python:    • Audio Data Processing in Python   Efficient Pandas Dataframes:    • Speed Up Your Pandas Dataframes   Youtube: https://youtube.com/@robmulla?sub_con... Discord:   / discord   Twitch:   / medallionstallion_   Twitter:   / rob_mulla   Kaggle: https://www.kaggle.com/robikscube #xgboost #python #machinelearning