Deeper Learning By Doing: Integrating Hands-On Research Projects Into A Machine Learning Course

Sebastian Raschka

Keywords: machine learning, deep learning, project-based learning

TL;DR: This paper discusses how project-based learning components (project proposal, report, oral presentation, and peer-reviewing) can be integrated into a deep learning lecture course.

Abstract: Machine learning has seen a vast increase of interest in recent years, along with an abundance of learning resources. While conventional lectures provide students with important information and knowledge, we also believe that additional project-based learning components can motivate students to engage in topics more deeply. In addition to incorporating project-based learning in our courses, we aim to develop project-based learning components aligned with real-world tasks, including experimental design and execution, report writing, oral presentation, and peer-reviewing. This paper describes the organization of our project-based machine learning courses with a particular emphasis on the class project components and shares our resources with instructors who would like to include similar elements in their courses.

Community Implementations: [ 3 code implementations](https://www.catalyzex.com/paper/deeper-learning-by-doing-integrating-hands-on/code)