Applied Machine Learning (Summer semester 2024)

Lecturer: Sara Todorovikj

Assistant: --

Contents: The main goal of this seminar is to learn how to perform a complete machine learning project from beginning to end. This includes data exploration and preparation, model training, performance evaluation, fine tuning, analysis, visualization, and presentation of results. While students learn about the different phases of a machine learning project, they also learn about different approaches, e.g. linear/polynomial models, support vector machines, (convolutional) neural networks. Each phase is accompanied by practical exercises in a programming environment.

Qualification goals:

• Understanding of the functionality and application of machine learning, data analysis and data processing methods.
• Knowledge of programming and workflow in the context of machine learning.

Requirements: Programming in Python

Target groups: Master Human Factors

OPAL:

Seminar

This seminar does not take place this semester.

  Time: --

  Place: --