Results for data science

Publications & Outputs

1. Exploring Novel Datasets and Methods for the Study of False Information

   Dearden, E., 1/04/2022, Lancaster University. 298 p.

   Research output: Thesis › Doctoral Thesis

2. Applications of machine learning in spectroscopy

   Meza Ramirez, C. A., Greenop, M., Ashton, L. & Rehman, I. U., 30/09/2021, In: APPLIED SPECTROSCOPY REVIEWS. 56, 8-10, p. 733-763 31 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

3. The real climate and transformative impact of ICT: A critique of estimates, trends and regulations

   Freitag, C., Berners-Lee, M., Widdicks, K., Knowles, B., Blair, G. & Friday, A., 10/09/2021, In: Patterns. 2, 9, 100340.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

4. Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies

   Finlay, S., 27/05/2021, 4th ed ed. Preston: Relativistic. 236 p.

   Research output: Book/Report/Proceedings › Book

5. Rethinking data-driven decision support in flood risk management for a big data age

   Towe, R., Dean, G., Edwards, E., Nundloll, V., Blair, G., Lamb, R., Hankin, B. & Manson, S., 1/12/2020, In: Journal of Flood Risk Management. 13, 4, 19 p., e12652.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

6. Web application for the simulation of experimental data

   Bernabeu, P., 2020

   Research output: Other contribution

7. Navigating Diverse Data Science Learning: Critical Reflections Towards Future Practice

   Elkhatib, Y., 11/12/2017, Cloud Computing Technology and Science (CloudCom), 2017 IEEE International Conference on. IEEE, p. 357-362 6 p.

   Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

8. Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies

   Finlay, S. M., 28/05/2017, 2nd ed. UK: Relativistic. 150 p.

   Research output: Book/Report/Proceedings › Book

9. Compatibility between livestock databases used for quantitative biosecurity response in New Zealand

   Jewell, C. P., van Andel, M., Vink, D. & McFadden, A., 06/2016, In: New Zealand Veterinary Journal. 64, 3, p. 158-164 7 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

10. Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods

    Finlay, S. M., 1/07/2014, London: Palgrave Macmillan. 260 p.

    Research output: Book/Report/Proceedings › Book