Webinar and in-person: Machine Learning for Time Series and Anomaly Detection
24/05/2023 The network group Data Analytics, Machine Learning and data centric workflows invites you to a hybrid seminar featuring Tina Koziol and Kay Sørbø from Wintershall Dea . They will explore the power of machine learning on time series data. Don't miss out on this great event. Join us on June 12.
n this talk, we explore the power of machine learning on time series data, with a focus on two use cases: traffic prediction and wellbore annulus leakage detection in the oil and gas industry.
Time series data can provide valuable insights in transportation, energy, and other fields. By leveraging machine learning techniques on time series data, we can make accurate predictions, uncover patterns, and gain valuable insights to drive evidence-based decision-making. In the context of traffic prediction, machine learning models can predict traffic patterns, optimize traffic management strategies, and improve the flow of traffic, leading to reduced congestion and enhanced quality of life.