README.md

References and resources for seminars

Relevant references and external materials supporting the seminars are provided below.

Seminars for day 1 - Spectral data

Francesca Zambon: Mapping spectral information by means of Spectral unit

Wright, J., Rothery, D. A., Balme, M. R., & Conway, S. J. (2019). Geology of the Hokusai quadrangle (H05), Mercury. Journal of Maps, 15(2), 509-520. https://doi.org/10.1080/17445647.2019.1625821

Zambon, F., Carli, C., Wright, J., Rothery, D. A., Altieri, F., Massironi, M., ... & Cremonese, G. (2022). Spectral Units Analysis of Quadrangle H05‐Hokusai on Mercury. Journal of Geophysical Research: Planets, 127(3), e2021JE006918. https://doi.org/10.1029/2021JE006918

Beatrice Baschetti: Exploration of Hyperspectral Datasets with Unsupervised Learning Techniques

Code:

https://github.com/beatricebs/CRISM-python-unsupervised-clustering

Books:

Jiawei Han, Micheline Kamber, Jian Pei, “Data Mining, concepts and techniques (Third Edition)” – 2012, Morgan Kaufmann Publishers (Elsevier)

Aurélien Géron, “Hands-on machine learning with Scikit-learn, Keras and Tensor Flow (Second Edition)” – 2019, O’Reilly Media

Andreas C. Müller and Sarah Guido, “Introduction to Machine Learning with Python” – 2017, O’Reilly Media

Links:

• SCIKIT-LEARN
  • https://scikit-learn.org/stable/modules/clustering.html#clustering
  • https://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html
• UMAP:
  • https://umap-learn.readthedocs.io/en/latest/
  • https://pair-code.github.io/understanding-umap/