Lab Machine Learning for Data Science (Implementation Project)

Course description: The course will consist of applying machine learning techniques for extracting domain insights from real-world or simulated datasets. It will take the form of multiple lab exercises in Python, where the students will extract data, apply visualization techniques, train machine learning models on this data, use model selection/validation techniques, and finally apply interpretability techniques to extract domain insights from the learned models.

Organization of the course: cf. here

Kick-off meeting: 19 April 2024 at 2:15pm in room T9/K 036 (Takustr. 9)

Recommended prior course: Machine Learning for Data Science

Format: Oral presentation at the end of the semester