Introduction to Machine learning in Python: Classification

An introduction to machine learning in Python focusing on classification (supervised learning)

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
Profilbilde
Instructor:?
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