TY - GEN
T1 - MLadder
T2 - 31st ACM International Conference on Information and Knowledge Management, CIKM 2022
AU - Han, Siqi
AU - Li, Wanting
AU - Zhang, En
AU - Shi, Jilin
AU - Wang, Wei
AU - Lu, Xuesong
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/10/17
Y1 - 2022/10/17
N2 - Education on machine learning and data science has drawn a lot of attention in both higher education and vocational training. Although various tools and services such as Jupyter Notebook and Google Cloud's AI have been developed for building and training models, they are not suitable for direct use in educational settings. For example, teachers expect a platform where they can easily distribute and grade programming assignments, and students want to quickly start coding and training models without the burden of setting up an environment. To this end, we develop MLadder, an online training system for machine learning and data science education. Specifically, we seamlessly integrate two open-source software, CodaLab and Jupyter Notebook, which are used for hosting assignments and building models, respectively. Moreover, we devise several methods to make the system lightweight and scalable, so that it can be deployed on-premises even with limited resources. We have used MLadder in the machine learning and data science courses in our school and facilitated both teaching and learning.
AB - Education on machine learning and data science has drawn a lot of attention in both higher education and vocational training. Although various tools and services such as Jupyter Notebook and Google Cloud's AI have been developed for building and training models, they are not suitable for direct use in educational settings. For example, teachers expect a platform where they can easily distribute and grade programming assignments, and students want to quickly start coding and training models without the burden of setting up an environment. To this end, we develop MLadder, an online training system for machine learning and data science education. Specifically, we seamlessly integrate two open-source software, CodaLab and Jupyter Notebook, which are used for hosting assignments and building models, respectively. Moreover, we devise several methods to make the system lightweight and scalable, so that it can be deployed on-premises even with limited resources. We have used MLadder in the machine learning and data science courses in our school and facilitated both teaching and learning.
KW - educational support
KW - kubernetes
KW - machine learning education
KW - online systems
UR - https://www.scopus.com/pages/publications/85140826026
U2 - 10.1145/3511808.3557201
DO - 10.1145/3511808.3557201
M3 - 会议稿件
AN - SCOPUS:85140826026
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 4862
EP - 4866
BT - CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
PB - Association for Computing Machinery
Y2 - 17 October 2022 through 21 October 2022
ER -