Credits and data sources
The chapters load their data from this site rather than from a third-party URL, so the same code runs here, on a local clone and on Colab — but only where the licence allows it. Those datasets are listed below with their source and licence, and with the citation they ask for where they ask for one. The two whose licence does not allow it are not served here: the chapters that use them download them from the URL their authors published, exactly as any reader of the page could.
The machine-readable version, with sizes and checksums, is in data/MANIFEST.yml.
Datasets
UCI Machine Learning Repository
All licensed CC BY 4.0.
| Dataset | Used in | Cite |
|---|---|---|
| Auto MPG | chapters 8, 10, 14, 20 | UCI Machine Learning Repository. DOI 10.24432/C5859H |
| Automobile | chapter 8 | UCI Machine Learning Repository |
| Breast Cancer Wisconsin (Diagnostic) | chapter 9 | Wolberg, Mangasarian, Street & Street, UCI Machine Learning Repository |
| SMS Spam Collection | chapters 16, 17 | Almeida, T.A., Gómez Hidalgo, J.M., Yamakami, A. Contributions to the Study of SMS Spam Filtering: New Collection and Results, DOCENG 2011 |
| Sentiment Labelled Sentences | chapter 17 | Kotzias, D., Denil, M., de Freitas, N., Smyth, P. From Group to Individual Labels using Deep Features, KDD 2015 |
CDC
| Dataset | Used in | Source |
|---|---|---|
| CDC Diabetes Health Indicators | chapter 13 | 2015 responses to the CDC Behavioral Risk Factor Surveillance System. A work of the US federal government, in the public domain in the United States |
Other sources
| Dataset | Used in | Source and licence |
|---|---|---|
| Google Play Store Apps | Python self-study (lab 3) | Scraped and published by Lavanya Gupta on Kaggle, lava18/google-play-store-apps, under CC BY-SA 4.0. Served here unmodified, under the same licence |
| Titanic passenger list | chapters 1–6 | Historical passenger records, which carry no copyright as facts. This CSV comes via agconti/kaggle-titanic (Apache-2.0); the underlying records are documented by Encyclopedia Titanica |
| LUCAS | chapter 11 | Causality Workbench, Guyon et al. — not served here, see below |
| Mall Customer Segmentation | chapter 18 | Kaggle, vjchoudhary7/customer-segmentation-tutorial-in-python — not served here, see below |
Height/weight and the student records are the teacher’s own course material.
Neither the LUCAS page nor the Mall Customers listing grants a licence, so we do not redistribute them: chapters 11 and 18 download them from the URL their authors published, exactly as any reader of the page could. If you hold rights in either and would rather they were not used at all, write to antonino.furnari@unict.it and they will be replaced.
Images and figures
Figures in the chapters are generated by the code beside them, or drawn by the scripts in figures/, and are the teacher’s own work. Images inherited from earlier editions of the course are being audited; anything found to belong to someone else is replaced or credited here.
The notes themselves
Written by Antonino Furnari for Fondamenti di Analisi dei Dati, BSc in Computer Science (L-31), University of Catania. Chapters that adapt a worked example from a textbook say so in their References section.
Parts of this material — prose, figures, code and the self-assessment questions — were drafted with the help of AI tools. Everything published here has been read, checked and edited by the teacher, who is responsible for its content: where a number appears in the text it comes from the code beside it, and where a claim is made it is the teacher’s.