Veröffentlichungen (Auszug)

2024

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2023

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2022

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2021

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2020

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2019

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2018

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2017

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2016

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2015

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2014

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks

2013

[182401]
Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em>
Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna
in: <em>DELFI 2020</em>. (2020).
Volume: Number:
on pages: 365-366
Chapter:
Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.)
Publisher: Gesellschaft für Informatik e.V.:
Series: Lecture Notes in Informatics (LNI) - Proceedings
Address: Bonn
Edition:
ISBN: 978-3-88579-702-9
how published:
Organization:
School:
Institution:
Type:
DOI:
URL: https://api.ltb.io/show/BMRWS
ARXIVID:
PMID:

[pdf] [www]

Note: malitup

Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks