Deeper Learning By Doing: Integrating Hands-On Research Projects Into a Machine Learning Course
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 1 of its 6 references that are in the map. First posted on arXiv 28 Jul 2021.
Builds on
1 of 6 references.
References · 1
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
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Citing papers per year: 2022: 1.
1 paper.
- 2022Machine Learning Students Overfit to Overfittingcited by 1
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