Tile: References | Big data

References
1. Mavridis, I., & Karatza, H. (2017). Performance evaluation of cloud-based log file analysis with Apache Hadoop and Apache Spark. Journal of Systems and Software, 125, 133-151. (https://doi.org/10.1016/j.jss.2016.11.037)
2. Aiello, S., Eckstrand, E., Fu, A., Landry, M., & Aboyoun, P. (2016). Machine Learning with R and H2O. H2O booklet, 550.
3. LeDell, E., & Poirier, S. (2020, July). H2O AutoML: Scalable automatic machine learning. In Proceedings of the AutoML Workshop at ICML (Vol. 2020).
4. H2O.ai, H2O Case Studies, https://h2o.ai/case-studies/. Accessed in March, 2023.
5. Landau, W.M. "The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing." Journal of Open Source Software 6, no. 57 (2021): 2959. (DOI: 10.21105/joss.02959)
6. Hyndman, R.J., & Athanasopoulos, G. (2021) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia. https://otexts.com/fpp3. Accessed in March, 2023.
7. Baghdadi, A., Lama, S., Singh, R., Hoshyarmanesh, H., Razmi, M., & Sutherland, G. R. (2021). A data-driven performance dashboard for surgical dissection. Scientific Reports, 11(1), 15013.