Logo des Repositoriums

Auflistung nach Schlagwort "Jupyter Notebooks"

1 - 2 von 2
  • Konferenzbeitrag
    MLProvCodeGen: A Tool for Provenance Data Input and Capture of Customizable Machine Learning Scripts
    (BTW 2023, 2023) Mustafa, Tarek Al; König-Ries, Birgitta; Samuel, Sheeba
    Over the last decade Machine learning (ML) has dramatically changed the application ofand research in computer science. It becomes increasingly complicated to assure the transparency and reproducibility of advanced ML systems from raw data to deployment. In this paper, we describe an approach to supply users with an interface to specify a variety of parameters that together provide complete provenance information and automatically generate executable ML code from this information. We introduce MLProvCodeGen (Machine Learning Provenance Code Generator), a JupyterLab extension to generate custom code for ML experiments from user-defined metadata. ML workflows can be generated with different data settings, model parameters, methods, and trainingparameters and reproduce results in Jupyter Notebooks. We evaluated our approach with two ML applications, image and multiclass classification, and conducted a user evaluation.
  • Konferenzbeitrag
    Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks
    (DELFI 2020 – Die 18. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V., 2020) Kastner, Marvin; Franzkeit, Janna; Lainé, Anna
    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.