Lecture Week 2024
11th Joint RS-APS & HGS-HIRe Lecture Week
Machine Learning from Scratch
In cooperation with the Helmholtz AI Consultant Team for Matter Research:
Predictive modeling brings value to a vast variety of data, in business intelligence, health, industrial processes and scientific discoveries. It is a pillar of modern data science. In this field, scikit-learn is a central tool: it is easily accessible, yet powerful, and naturally dovetails in the wider ecosystem of data-science tools based on the Python programming language.
Content: The course is an in-depth introduction to predictive modeling with scikit-learn. Step-by-step and didactic lessons introduce the fundamental methodological and software tools of machine learning, and is as such a stepping stone to more advanced challenges in artificial intelligence, text mining, or data science. The course is more than a cookbook and teaches to be critical about each step of the design of a predictive modeling pipeline: from choices in data preprocessing, to choosing models, gaining insights on their failure modes and interpreting their predictions.
Target group: The course is tailored to machine learning beginners. With a decent python coding background, the participant is well equipped for the course.
Registration: For registration please send a brief e-mail to rsaps(at)hi-jena.gsi.de or info(at)hgs-hire.de as soon as possible. Please indicate in your registration e-mail your affiliation and whether you need accommodation.
Begin/End: The lecture week starts on Monday, November 25th at 09:00 a.m. with a welcome and the first lecture (please note possible changes), see also timetable below. Please arrange your travel accordingly. The lecture week ends on Thursday at 12:00 after the participant poster session.
Venue: The lecture week will take place as a face-to-face event at the Friedrich Schiller University Jena: Seminar room E012 in "Rosensälen" Fürstengraben 27 and seminar room in "Accouchierhaus" Jenergasse 8. Directions on google maps >
The participant poster session will take place in the new building of the Helmholtz Institute Jena, Fraunhofer Straße 8. Directions on google maps>
Travel: Please arrange your travel to/from the venue individually by public transport (train & bus) or by car pool. Please make sure to arrive well in time. In case you need accommodation please make sure to indicate this in your registration.
Food: Lunch and snacks during the lectures is included in the lecture week. Special food (vegetarian, other) is available.
What to bring: Equipment needed for the exercises: The exercises will include programming. For this you will need to have a laptop with you including working installations of Python.
Participant poster session: Please bring a poster of your own research for the participant poster session. There is no need to print a new one, you may reuse one of a past workshop or conference.
Internet: Wireless internet access is available at the venue
Clothing: The lecture week will be informal, so only casual clothing is needed.
Expenses: All basic expenses including accommodation (with breakfast) are covered by RS-APS and HGS-HIRe. You only have to pay for dinner and local expenses.
Social program: A visit of a show in the planetarium Jena is scheduled for Thursday at 5:30 p.m.. Directions on google maps>
Insurance: Though this trip will not generate any costs for your supervisor or group please do not forget to file a trip request so you are covered by insurance during the lecture week. Please ask the secretary of your official supervisor at the university for the appropriate form.
