# Bibliography

Bishop, C. M. 2006. Pattern Recognition and Machine Learning. Springer. https://www.microsoft.com/en-us/research/people/cmbishop/prml-book/.

Härdle, W. K., and L. Simar. 2015. Applied Multivariate Statistical Analysis. Berlin: Springer.

Hastie, T., R. Tibshirani, and J. Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. Springer. https://web.stanford.edu/~hastie/ElemStatLearn/.

James, G., D. Witten, T. Hastie, and R. Tibshirani. 2013. An Introduction to Statistical Learning with Applications in R. Springer. https://www.statlearning.com.

———. 2021. An Introduction to Statistical Learning with Applications in R. 2nd ed. Springer. https://www.statlearning.com.

Marden, J. I. 2015. Multivariate Statistics: Old School. CreateSpace. http://stat.istics.net/Multivariate.

Murphy, K. P. 2012. Machine Learning: A Probabilistic Perspective. MIT Press.

Rogers, S., and M. Girolami. 2017. A First Course in Machine Learning. 2nd ed. Chapman; Hall / CRC.

Zhang, A., Z. C. Lipton, M. Li, and A. J. Smola. 2020. Dive into Deep Learning. https://d2l.ai.