References#

Books#

• Provost, F., & Fawcett, T. (2013). Data Science for Business. O'Reilly Media.

• Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer.

• James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R. Springer.

Scientific Articles#

• Kohavi, R., & Longbotham, R. (2017). Online Controlled Experiments and A/B Testing: Identifying, Understanding, and Evaluating Variations. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1305-1306). ACM.

• Caruana, R., & Niculescu-Mizil, A. (2006). An empirical comparison of supervised learning algorithms. In Proceedings of the 23rd International Conference on Machine Learning (pp. 161-168).