2 Combining dynamic models with deep learning through time series analysis

Abstract Time series analysis is a traditional approach to analyzing a sequence of data. This approach allows us to study the trend over time, discover the temporal dependencies, and analyze the fluctuations within the data. An understanding of the underlying data generative process can lead to better forecast and decision-making. The time series application can be found across diverse domains including animal sciences, economics, and environmental sciences. In this talk, we will present the fundamental concepts of time series and traditional and state-of-the-art approaches for analyzing such data. By providing a comprehensive overview of time series analysis, this talk aims to equip the audience with a foundational understanding and practical insights into harnessing the power of temporal data and the use of mathematical models that inform and improve decision-making in animal production settings.