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263-5052-00L 5 Credits MSC , WBZ D-ITET , D-INFK , D-MATH
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Interactive Machine Learning: Visualization & Explainability

Lecturers & Examiners: Prof. Dr. Menna El-Assady
VVZ CR 3.4

Last Updated: 2026-06-01 11:33:07

Abstract

Visual Analytics supports the design of human-in-the-loop interfaces that enable human-machine collaboration. In this course, will go through the fundamentals of designing interactive visualizations, later applying them to explain and interact with machine leaning models.

Objective

The goal of the course is to introduce techniques for interactive information visualization and to apply these on understanding, diagnosing, and refining machine learning models.

Content

Interactive, mixed-initiative machine learning promises to combine the efficiency of automation with the effectiveness of humans for a collaborative decision-making and problem-solving process. This can be facilitated through co-adaptive visual interfaces. This course will first introduce the foundations of information visualization design based on data charecteristics, e.g., high-dimensional, geo-spatial, relational, temporal, and textual data. Second, we will discuss interaction techniques and explanation strategies to enable explainable machine learning with the tasks of understanding, diagnosing, and refining machine learning models. Tentative list of topics: 1. Visualization and Perception 2. Interaction and Explanation 3. Systems Overview

Resources

Lecture Notes

Course material will be provided in form of slides.

Literature

Will be provided during the course.

Learning Materials (Links)

General Information

Language
English
Levels
MSC , WBZ
Frequency
Yearly recurring

Examination

Type
end-of-semester examination
Mode
written 120 minutes
Aids
None
Final grade: 50% written exam, 50% mandatory project work

Registration & Places

Max Places
190
Priority: Registration for the course unit is until 02.03.2025 only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture with exercise Interactive Machine Learning: Visualization & Explainability
  • Thu 11:15-14:00 (CAB G 61)
3 h weekly
independent project Interactive Machine Learning: Visualization & Explainability No time listed 1 h weekly

Offered In