Time and place:
The course consists of two sessions:
Wednesday April 17th, 09:15-12:00, in seminar room Prolog, Ole-Johan Dahls hus
Friday April 19th, 09:15-12:00, in seminar room Prolog, Ole-Johan Dahls hus
Language:
English
Target audience:
UiO reseachers and students who want to get started with machine learning in R.
A video (approximately 25 minutes) has been prepared that might be useful for those that are completely new to machine learning, with example use-cases in research.
Prerequisites:
It is an advantage but not necessary that you are accustomed to writing code in R. Basic knowledge of descriptive statistics and tidyverse is a plus.
Contents:
- Exploratory data analysis
- Binary classification
- Feature importance
- Multiclass classification
- Cross-validation
- Additional topics
- Preprocessing data with "recipe"
- Building and evaluating multiple models
simultaneously - Statistically comparing models
- Hyperparamater tuning
- Predicting a continuous variable
Luigi Maglanoc
Briefly about the course:
The focus will be on building and evaluating machine learning models in R rather than an in-depth breakdown of specific algorithms. We will be building models to distinguish between different categories of text based on l