Time and place:
The course consists of two sessions:
Monday 6th, 12:15-15:00, in seminar room Java, Ole-Johan Dahls hus
Wednesday May 8th, 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 Python.
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:
Some familiary with Python is required (i.e. you can run python scripts from the REPL or an IDE). Basic knowledge of descriptive statistics and pandas is a plus.
Contents:
- Exploratory data analysis
- Binary classification
- Feature importance
- Multiclass classification
- Cross-validation
- Additional topics
- Preprocessing and pipelines
- Statistically comparing models
- Hyperparamater tuning
- Predicitng a continuous variable
Luigi Maglanoc
Briefly about the course:
The focus will be on building and evaluating machine learning models in Python rather than an in-depth breakdown of speci