Publisher
Springer International Publishing
Reference23 articles.
1. Ahmed, B., Dannhauser, T., Philip, N.: A lean design thinking methodology (LDTM) for machine learning and modern data projects. In: 10th Computer Science and Electronic Engineering Conference, CEEC, pp. 11–14 (2019). https://doi.org/10.1109/CEEC.2018.8674234
2. Angée, S., Lozano-Argel, S.I., Montoya-Munera, E.N., Ospina-Arango, J.D., Tabares-Betancur, M.S.: Towards an improved ASUM-DM process methodology for cross-disciplinary multi-organization big data & analytics projects. Commun. Comput. Inf. Sci. 613–624 (2018). https://doi.org/10.1007/978-3-319-95204-8_51, https://www.researchgate.net/publication/326307750
3. Costa, C.J., Aparicio, J.T.: POST-DS: A methodology to boost data science. In: Iberian Conference on Information Systems and Technologies, CISTI, pp. 24–27 (2020). https://doi.org/10.23919/CISTI49556.2020.9140932
4. Dåderman, A., Rosander, S.: Evaluating frameworks for implementing machine learning in signal processing: a comparative study of CRISP-DM, SEMMA and KDD. Technical report (2018). https://www.diva-portal.org/smash/get/diva2:1250897/FULLTEXT01.pdf
5. Foroughi, F., Luksch, P.: Data science methodology for cybersecurity projects. In: 5th International Conference on Artificial Intelligence and Applications, pp. 1–14 (2018). https://doi.org/10.5121/csit.2018.80401
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献