The course focuses on applying machine learning, as well as systems engineering knowledge to hands-on problems in computer vision, data mining and to study intelligent software systems.
We will be going through techniques ranging from traditional machine learning up to recent state-of-the-art neural network based deep learning methods and apply them to a diverse set of case studies.
Internship sessions will feature introductions to machine learning software and platforms, data visualization, supervised and unsupervised machine, reinforcement and deep learning methods such as random forests, clustering, artificial neural networks and deep neural networks (convolutional neural networks, recurrent neural networks, auto encoders , variational/generative models).
Towards the end of the internship students will apply their acquired practical knowledge in projects. Students will gather in small groups, pick project topics and present their efforts at the end of the semester.
- Trainer/in: Achref Jaziri
- Trainer/in: Visvanathan Ramesh
- Trainer/in: Konrad Wartke