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Teaching ML
2020
2022
2020
2022
Keyphrases
Publications
2022
Matias Valdenegro-Toro
,
Matthia Sabatelli
Machine Learning Students Overfit to Overfitting.
Teaching ML
(2022)
Ludwig Bothmann
,
Sven Strickroth
,
Giuseppe Casalicchio
,
David Rügamer
,
Marius Lindauer
,
Fabian Scheipl
,
Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science.
Teaching ML
(2022)
Gero Szepannek
,
Laurens Martin Tetzlaff
,
Alexander Frahm
,
Karsten Lübke
Teaching Machine Learning with mlr3 using Shiny.
Teaching ML
(2022)
Gulustan Dogan
Teaching Machine Learning with Applied Interdisciplinary Real World Projects.
Teaching ML
(2022)
Ken Hasselmann
,
Quentin Lurkin
Stimulating student engagement with an AI board game tournament.
Teaching ML
(2022)
Lukas Lodes
,
Alexander Schiendorfer
A Deep Learning Bootcamp for Engineering & Management Students.
Teaching ML
(2022)
Donatella Cea
,
Helene Hoffmann
,
Marie Piraud
Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds.
Teaching ML
(2022)
Tilman Michaeli
,
Stefan Seegerer
,
Lennard Kerber
,
Ralf Romeike
Data, Trees, and Forests - Decision Tree Learning in K-12 Education.
Teaching ML
(2022)
Jan Ebert
,
Danimir T. Doncevic
,
Ramona Kloß
,
Stefan Kesselheim
Hearts Gym: Learning Reinforcement Learning as a Team Event.
Teaching ML
(2022)
Florian Huber
,
Erica Dafne van Kuppevelt
,
Peter Steinbach
,
Colin Sauze
,
Yang Liu
,
Berend Weel
Will the sun shine? - An accessible dataset for teaching machine learning and deep learning.
Teaching ML
(2022)
volume 207, 2022
The Third Teaching Machine Learning and Artificial Intelligence Workshop, 19-23 September 2022, Grenoble, France and online.
Teaching ML
207 (2022)
2021
Alfredo Canziani
Teaching Deep Learning, a boisterous ever-evolving field.
Teaching ML
(2021)
Hilde Jacoba Petronella Weerts
,
Mykola Pechenizkiy
Teaching Responsible Machine Learning to Engineers.
Teaching ML
(2021)
Rabea Müller
,
Akinyemi Mandela Fasemore
,
Muhammad Elhossary
,
Konrad U. Förstner
A lesson for teaching fundamental Machine Learning concepts and skills to molecular biologists.
Teaching ML
(2021)
Daniel van Strien
,
Mark Bell
,
Nora Rose McGregor
,
Michael Trizna
An Introduction to AI for GLAM.
Teaching ML
(2021)
Matias Valdenegro-Toro
Teaching Uncertainty Quantification in Machine Learning through Use Cases.
Teaching ML
(2021)
Sarah M. Brown
Participatory Live Coding and Learning-Centered Assessment in Programming for Data Science.
Teaching ML
(2021)
Martin Palazzo
,
Agustin Velazquez
,
Melisa Breda
,
Matias Callara
,
Nicolas Aguirre
Teaching Machine Learning in Argentina: the ClusterAI pipeline.
Teaching ML
(2021)
Ting-Wu Chin
,
Dimitrios Stamoulis
,
Diana Marculescu
Putting the "Machine" Back in Machine Learning for Engineering Students.
Teaching ML
(2021)
Patrick O. Glauner
Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses.
Teaching ML
(2021)
Jónathan Heras
Deep Learning Projects from a Regional Council: An Experience Report.
Teaching ML
(2021)
Oliver Guhr
,
Katherine M. Kinnaird
,
Peter Steinbach
Teaching ML in 2021 - An Overview and Introduction.
Teaching ML
(2021)
Viviana Acquaviva
Teaching Machine Learning for the Physical Sciences: A summary of lessons learned and challenges.
Teaching ML
(2021)
Erik Marx
,
Thiemo Leonhardt
,
David Baberowski
,
Nadine Bergner
Using Matchboxes to Teach the Basics of Machine Learning: an Analysis of (Possible) Misconceptions.
Teaching ML
(2021)
Omar Shouman
,
Simon Fuchs
,
Holger Wittges
Experiences from Teaching Practical Machine Learning Courses to Master's Students with Mixed Backgrounds.
Teaching ML
(2021)
Hussain Kazmi
Teaching machine learning through end-to-end decision making.
Teaching ML
(2021)
Carrie Diaz Eaton
Teaching Machine Learning in the Context of Critical Quantitative Information Literacy.
Teaching ML
(2021)
Sebastian Raschka
Deeper Learning By Doing: Integrating Hands-On Research Projects Into A Machine Learning Course.
Teaching ML
(2021)
volume 170, 2021
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, September 8+13, 2021, Virtual Conference.
Teaching ML
170 (2021)
2020
Alexander Schiendorfer
,
Carola Gajek
,
Wolfgang Reif
Turning Software Engineers into Machine Learning Engineers.
Teaching ML
(2020)
Miriam Elia
,
Carola Gajek
,
Alexander Schiendorfer
,
Wolfgang Reif
An Interactive Web Application for Decision Tree Learning.
Teaching ML
(2020)
Daniela Huppenkothen
,
Gwendolyn Eadie
Teaching the Foundations of Machine Learning with Candy.
Teaching ML
(2020)
Peter Steinbach
,
Heidi Seibold
,
Oliver Guhr
Teaching Machine Learning in 2020.
Teaching ML
(2020)
Katherine M. Kinnaird
Teaching Computational Machine Learning (without Statistics).
Teaching ML
(2020)
Claudia Engel
,
Nicole Coleman
AI is not Just a Technology.
Teaching ML
(2020)
Javier García-Algarra
Introductory Machine Learning for non STEM students.
Teaching ML
(2020)
volume 141, 2020
Proceedings of the First Teaching Machine Learning and Artificial Intelligence Workshop, September 8+14, 2020, Virtual Conference.
Teaching ML
141 (2020)