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Walk through a time series forecasting example using Python and XGBoost to predict energy consumption. Learn data preparation techniques, feature creation, model building, and feature importance analysis. Follow along with a Kaggle notebook to gain hands-on experience in applying machine learning to time series data. Explore the entire process from data preprocessing to generating forecasts, with a focus on using XGBoost for accurate predictions.
Syllabus
Intro
Data prep
Feature creation
Model
Feature Importance
Forecast
Taught by
Rob Mulla