**Forecasting **is one of the process of predicting the future based on past and present data. Most of the forecasting problem associated with time series data (i.e. what is the sale of product A next month).Some problems can be easier to forecast than others. The predictability of an event or a quantity depends on several factors, some are:

  1. understanding of the factors contribute to the result;data availability;forecasting technique or learning algorithm.

Often, there are many methods in solving forecast accurately, good forecasts capture the genuine patterns and relationships which exist in the historical data, but do not replicate past events that will not occur again.

Seasonality and use cases

In time series data, seasonality refers to the presence of some certain regular intervals, or predictable cyclic variation depending on the specific time frame (i.e. weekly basis, monthly basis). Some examples of seasonality is higher sales during Christmas, higher bookings during holiday period.

#machine-learning #time-series-analysis #fourier-transform #artificial-intelligence #python

Seasonality Detection with Fast Fourier Transform (FFT) and Python
26.50 GEEK