Speaker
Description
Time series analysis is a powerful tool used to extract insights from data collected over time, and its applications span across a wide range of fields of application. By analysing trends, patterns, and seasonal variations, time series models allow for accurate forecasting and anomaly detection. Beyond forecasting, classifying time series data allows us to group similar patterns and behaviors, adding even more depth to its utility. Moreover, the methodologies applied in one area can often be adapted to others, allowing knowledge sharing and innovation across different domains. In this talk, we will explore how the same methodologies used to analyse temporal data can be used in seemingly unrelated fields, highlighting how innovations in one area can provide valuable insights and solutions in others.