Deeper Learning By Doing: Integrating Hands-On Research Projects Into a Machine Learning 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.
Cite
@article{arxiv.2107.13671,
title = {Deeper Learning By Doing: Integrating Hands-On Research Projects Into a Machine Learning Course},
author = {Sebastian Raschka},
journal= {arXiv preprint arXiv:2107.13671},
year = {2021}
}
Comments
This paper was accepted to the Teaching Machine Learning Workshop at ECML 2021 (https://teaching-ml.github.io/2021/). Reviews and comments are available at https://openreview.net/forum?id=yFPqbprG2Qb¬eId=rSPC7tA6Pi_