Malvika Sharan, Bernd Klaus, Georg Zeller (HD-HuB), Bernd Bischl, Xudong Sun, Michel Lang (Ludwig-Maximilians-University Munich)
12/06/2018 - 13/06/2018
09:30 - 17:00
This two-day course, delivered by experts in programming for data analysis, will teach participants the principle of machine learning and its implementation in R using mlr package. 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. The schedule and course materials will be added here.
Prior to the course, on June 11 2018, 2:00 PM at Small Operon, an open seminar will be delivered by Prof. Bernd Bischl who will talk about Machine Learning,mlr package and openML project.
This 2-day course will cover the following topics and sessions:
– A brief introduction to Machine Learning
– mlr package and its application
– Linear models and regularization
– Trees, forests and boosting
– Tuning and nested resampling
– Interpretable machine learning and feature selection
– Application to microbiome-based cancer detection
– Evaluation (training and testing) and cross-validation with replicates
– OpenML project with its demo
– Open question sessions
The main goal of this course is to provide insides into machine learning tasks as classification, regression, cluster analysis and survival analysis in R.
The course is aimed at participants with experience of R scripting, preferably with some knowledge of machine learning and want to learn more about its application and implementation through the hands-on sessions and use cases. The participants are suggested to check these materials before the workshop.
Participants are expected to bring their own laptop with R version >=3.3.2 installed.
R, mlR, Machine Learning
Please note that the maximum capacity for the course is 30 participants and registration is required to secure a place.
This course will be offered for free to all EMBL members. The external participants will be charged with a course fee of 100 Euro. The invoice details will be shared via email. The registration can be canceled for the free of charge until June 2, 2018. The participants will be charged a cancellation fee (if canceled after June 2, 2018) or no-show fee of 50 Euros. The invoice details will be shared via email.