Time Series Forecasting Using Past and Future Data

When doing time series forecasting, it is important to have a good understanding of the external data that will be used to predict future events. This understanding can be gained by looking at past data and analyzing how it relates to future events. Additionally, one can use future data to understand potential trends and patterns. By doing this, one can develop models that are more accurate in predicting future outcomes.

Here’s a list of past/future data to look out for:

✅Known weather conditions and forecasts

✅Economic indicators (GDP Growth, unemployment rates, inflation rates)

✅Known local events and upcoming bank holidays

✅Known/confirmed hotel bookings

By understanding these patterns, analysts can make better predictions about when conditions are likely to worsen or improve.

Matt von Rohr
Matt von Rohr

#ai #datascience #machinelearning #dataengineering #dataintegration

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