Uploaded August 2022 | Updated September 2026, 2 hours ago

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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: youtu.be/vV12dGe_Fho
The notebook used in this video here: kaggle.com/code/robikscube/pt2-time-series-forecasting-with-xgboost/notebook

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: twitch.tv/medallionstallion_

My other videos:

Speed Up Your Pandas Code: youtube.com/watch?v=SAFmrTnEHLg
Speed up Pandas Code: youtube.com/watch?v=SAFmrTnEHLg
Intro to Pandas video: youtube.com/watch?v=_Eb0utIRdkw
Exploratory Data Analysis Video: youtube.com/watch?v=xi0vhXFPegw

Working with Audio data in Python: youtube.com/watch?v=ZqpSb5p1xQo
Efficient Pandas Dataframes: youtube.com/watch?v=u4_c2LDi4b8

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* Kaggle: kaggle.com/robikscube

#xgboost #python #machinelearning