| Referências: |
Grus, J. (2015). Data Science from Scratch: First Principles with Python. O’Reilly. https://github.com/joelgrus/data-science-from-scratch.
Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, Vipin Kumar (2019). Introduction to Data Mining (Second Edition). Pearson. https://www.pearson.com/us/higher-education/program/Tan-Introduction-to-Data-Mining-2nd-Edition/PGM214749.html
Daniel T. Larose and Chantal Larose (2014). Discovering Knowledge in Data: An Introduction to Data Mining. 2nd Ed., Wiley. Link: http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470908742.html
Livros complementares:
1. Kohonen, T. (2001). Self-Organizing Maps, 3rd Ed., Springer, Berlin. http://www.springer.com/la/book/9783540679219
2. Kohonen, T. (2014). MATLAB Implementations and Applications of the Self-Organizing Map. Unigrafia. Helsinki, Finland, 2014. URL http://docs.unigrafia.fi/publications/kohonen_teuvo/MATLAB_implementations_and_applications_of_the_self_organizing_map.pdf
3. Johnsson, M. Applications of Self-Organizing Maps, ISBN 978-953-51-0862-7, 298 pages, Publisher: InTech, 2012. URL http://www.intechopen.com/books/applications-of-self-organizing-maps
4. Theodoridis, S. and Koutroumbas, K. (2005). Pattern Recognition - 3th Edition - Elsevier Academic Press.
5. Duda, R. O., Hart, P.E., and Stork, D.G. (2001). Pattern Classification, 2nd ed. Wiley Interscience, ISBN: 0-471-05669-3.
6. S. Haykin, Neural Networks: A Comprehensive Foundation (Second Edition), Macmillan, New York, NY, 1999.
Outros textos:
Artigos científicos a serem distribuídos durante o curso, ex:
• A.K. Jain, R.P.W. Duin and J. Mao, "Statistical pattern recognition: a review," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, 2000, 4-37.
• K. Jain, M.N. Murthy and P.J. Flynn, Data Clustering: A Review, ACM Computing Reviews, Nov 1999. Disponível em http://dataclustering.cse.msu.edu/
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