Machine learning and deep learning
Data-driven approaches to solve a variety of scientific problems have been very successful in recent decades due to the availability of large amounts of data sets.
Machine Learning (ML) and Deep Learning (DL) techniques in particular are the most popular approaches. In this context, we will have an introduction to ML and DL models. We will talk about the computational cost of obtaining such models and the use of GPUs to speed
up the process. We also discuss some examples of ML/DL applied in engineering and the interests of nearby companies (e.g. Linak and Danfoss) to integrate these tools into their processes.
Wrapped sandwiches will be served during the presentation.
The presentation will be in English and is made in collaboration with SFA.
Presenter:
Fannia Pacheco is a post-doctoral fellow at the Department of Mechanical and Electrical Engineering at the University of Southern Denmark since 2020.
She received her PhD degree in Computer Science in 2019 from l'Université de Pau et des Pays de l'Adour, France.
She was a member of the GIDTEC research team at theUniversidad Politécnica Salesiana (UPS), Ecuador. Her researchinterests cover condition monitoring, data analysis and intelligent systems.
This event is closed for registration.
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