Teaching ML in 2021 - An Overview and Introduction

Oliver Guhr, Katherine M. Kinnaird, Peter Steinbach; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:1-4

[abs][Download PDF]

Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses

Patrick Glauner; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:5-9

[abs][Download PDF]

Teaching machine learning through end-to-end decision making

Hussain Kazmi; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:10-14

[abs][Download PDF]

Deep Learning Projects from a Regional Council: An Experience Report

Jónathan Heras; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:15-19

[abs][Download PDF]

An Introduction to AI for GLAM

Daniel van Strien, Mark Bell, Nora Rose McGregor, Michael Trizna; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:20-24

[abs][Download PDF]

Using Matchboxes to Teach the Basics of Machine Learning: an Analysis of (Possible) Misconceptions

Erik Marx, Thiemo Leonhardt, David Baberowski, Nadine Bergner; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:25-29

[abs][Download PDF]

Teaching Deep Learning, a boisterous ever-evolving field

Alfredo Canziani; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:30-34

[abs][Download PDF]

Teaching Machine Learning for the Physical Sciences: A summary of lessons learned and challenges

Viviana Acquaviva; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:35-39

[abs][Download PDF]

Teaching Responsible Machine Learning to Engineers

Hilde Jacoba Petronella Weerts, Mykola Pechenizkiy; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:40-45

[abs][Download PDF]

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

Sebastian Raschka; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:46-50

[abs][Download PDF]

Teaching Machine Learning in the Context of Critical Quantitative Information Literacy

Carrie Diaz Eaton; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:51-56

[abs][Download PDF]

Teaching Uncertainty Quantification in Machine Learning through Use Cases

Matias Valdenegro-Toro; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:57-61

[abs][Download PDF]

Experiences from Teaching Practical Machine Learning Courses to Master’s Students with Mixed Backgrounds

Omar Shouman, Simon Fuchs, Holger Wittges; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:62-67

[abs][Download PDF]

A lesson for teaching fundamental Machine Learning concepts and skills to molecular biologists

Rabea Müller, Akinyemi Mandela Fasemore, Muhammad Elhossary, Konrad U. Förstner; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:68-72

[abs][Download PDF]

Participatory Live Coding and Learning-Centered Assessment in Programming for Data Science

Sarah M. Brown; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:73-77

[abs][Download PDF]

Putting the "Machine" Back in Machine Learning for Engineering Students

Rudy Chin, Dimitrios Stamoulis, Diana Marculescu; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:78-82

[abs][Download PDF]

Teaching Machine Learning in Argentina: the ClusterAI pipeline

Martin Palazzo, Agustin Velazquez, Melisa Breda, Matias Callara, Nicolas Aguirre; Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:83-87

[abs][Download PDF]