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A forecast with honest error bars

Predict a real series, and be clear about how wrong you might be.

intermediatePython~24h

Why it matters

Forecasting is where naive evaluation does the most damage, because a random train-test split leaks the future. Getting the backtest right is the whole skill.

What you build

  • A naive baseline to beat
  • Backtesting that respects time order
  • Prediction intervals, not just points
  • An error metric appropriate to the series

If you want more

  • Add multiple seasonalities
  • Add holiday effects

Build it 5 steps

  • Surprisingly hard to beat. That is the point of doing it first.

  • Choose and justify the error metric

Material for the whole build

Shows you understand temporal leakage, which is the mistake that makes most forecasting portfolios worthless.

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