- Prof Bernd Bischl
- Martin Binder
- Giuseppe Casalicchio Affiliation: Ludwig-Maximilians-University Munich
This two-day course, on the implementation of Machine Learning in R, using mlr package will be delivered as practical sessions on programming and data analysis. The main goal of
mlr is to provide a unified interface for machine learning tasks as classification, regression, cluster analysis and survival analysis in R. Sessions will be driven by many practical exercises and case studies. Before this workshop, participants are expected to review the official material introducing the principle of Machine Learning (see the prerequisite).
This 2-day course will cover hands-on sessions using `mlr` and other relevant packages.
- 09:30-12:30 3h morning, 90 min Theory + 90 min Practical - 12:30-13:30 1h Lunchbreak - 13:30-16:30 3h afternoon, 90 min Theory + 90 min Practical - 16:30-17:00 Time for general questions
Introduction to the concepts and Practical with mlr - Performance Evaluation and Resampling (Metrics, CV, ROC) - Introduction to Boosting
Introduction to the concepts and Practical with mlr - Tuning and Nested Cross-Validation - Regularization and Feature Selection
The course is aimed at advanced R programmers, preferably with some knowledge of statistics and data modeling (See prerequisite materials from Day-1, 2, & 4). In this course, our learners will learn more about machine learning and its application and implementation through the hands-on sessions and use cases.
Anna Kreshuk (EMBL Group Leader) will lead a one-day discussion-based session on 14 October 2019 to address your questions on the prerequisite materials on the principle of Machine Learning. This will also allow you to connect with other participants of this workshop informally, and discuss the materials in smaller groups. Please register for this workshop separately: https://bio-it.embl.de/events/machine-learning-discussion-workshop-2019/.
Please register on this page: https://bio-it.embl.de/events/machine-learning-in-r-2019/
Please note that the maximum capacity of this course is 40 participants and registration is required to secure a place. If you have any questions, please contact Malvika Sharan. In your registration, please mention your EMBL group name, or institute's name (e.g. DKFZ, Uni-HD) if you are registering as an external participant.