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Time Series

via Kaggle

Overview

Apply machine learning to real-world forecasting tasks.
  • Use two features unique to time series: lags and time steps.
  • Model long-term changes with moving averages and the time dummy.
  • Create indicators and Fourier features to capture periodic change.
  • Predict the future from the past with a lag embedding.
  • Combine the strengths of two forecasters with this powerful technique.
  • Apply ML to any forecasting task with these four strategies.

Syllabus

  • Linear Regression With Time Series
  • Trend
  • Seasonality
  • Time Series as Features
  • Hybrid Models
  • Forecasting With Machine Learning

Taught by

Ryan Holbrook

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