Time series data allows us to analyze and understand changes and fluctuations over time, which can help with forecasting, detecting anomalies, and identifying the impact of events or interventions. It is a critical tool for businesses, governments, and researchers in a variety of domains.
In part 2 of our webinars on synthetic time series data (click here for part 1) we give an overview of traditional methods for data generation, covering their shortcomings and motivate the need for deep generative models. Following this, we give an introduction into the techniques and models used at the forefront of machine learning and data science for time series generation.
