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Bibliografía básica
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Fernández-Casal, R. y Costa, J. (2020). Aprendizaje Estadístico. Libro online: https://rubenfcasal.github.io/aprendizaje_estadistico
James, G., Witten, D., Hastie, T. y Tibshirani, R. (2017). An Introduction to Statistical Learning: with Aplications in R. Springer
Kuhn, M. y Johnson, K. (2013). Applied predictive modeling. Springer
Williams, G. (2011). Data Mining with Rattle and R. Springer
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Bibliografía complementaria
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Burger, S. V. (2018). Introduction to Machine Learning with R: Rigorous Mathematical Analysis. O’Reilly
Efron, B. y Hastie, T. (2016). Computer Age Statistical Inference. Cambridge University Press
Hastie, T., Tibshirani, R. y Friedman, J. (2017). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer
Hastie, T., Tibshirani, R. y Wainwright, M. (2015). Statistical Learning with Sparsity: the Lasso and Generalizations. CRC press
Torgo, L. (2011). Data Mining with R: Learning with Case Studies. Chapman & Hall/CRC Press
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Asignaturas