Intensive 3-Day Workshop with Lectures, Demos, and Exercises
This workshop is intended for students, researchers, and practitioners with basic experience in data science and machine learning who want to take their skills to the next level. This intensive workshop will give you the theoretical knowledge and practical skills to apply machine learning and data science techniques in practical contexts to analyze data, build predictive models, and optimize their performance.
Prof. Bernd Bischl leads the computational statistics group at LMU Munich and directs the Munich Center for Machine Learning. He is one of the principal authors of the mlr Machine Learning package, which the other presenters also contribute to. All presenters have extensive experience developing machine learning and data science approaches and applying them to real-world problems.
The mlr package is the most comprehensive machine learning package in R and has a rapidly growing user base. It is installed more than 15,000 times per month and the source code repository has more than 1,200 stars on GitHub. Version 3 is a complete reimplementation that takes the many lessons learned with previous versions into account to make machine learning easier, more flexible, and more efficient.
Tuesday, September 24
Wednesday, September 25
Thursday, September 26
In addition to the main workshop program, the presenters will be available on Friday September 27 to consult on individual and specific data science and machine learning problems by appointment only. To make such an appointment, please contact the organizer Lars Kotthoff at firstname.lastname@example.org and provide details of what you would like to consult on.
You must have R and mlr installed before the workshop — we will not provide any help with this during the workshop. You should have basic familiarity with programming and R. You can find a list of curated resources on how to install and get started with R at https://www.rstudio.com/online-learning/.
You should be familiar with basic concepts in data science and machine learning. We will assume that you know the material that is covered in the first two days of the online introduction to machine learning course you can find at https://compstat-lmu.github.io/lecture_i2ml/articles/content.html. The course provides lecture videos, slides, and exercises with solutions. Please work through this material before September 24; otherwise you will not be able to follow the material presented in the workshop. Your main focus should be on understanding the theoretical concepts; the exercises serve to illustrate them.
The workshop is open to everyone, regardless of whether affiliated with the University of Wyoming or not. Registration is free, but mandatory. Please register your interest at https://forms.gle/n88ehcP3wGc1MoZa9 by September 1. Registrations will be accepted on a first-come, first-serve basis until spaces are filled. If there are more registrations than spaces, preference will be given to people who have a background in data science or machine learning. You will receive an e-mail confirmation of your registration or notice that the workshop is full after the registration deadline; until then you are not registered.