Bibliografia

Principal

  • Shan, C., Wang, H., Song, M. and Chen, W. (2015) The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists Data Science Bookshelf
  • 7. Shan, Carl; Wang, Henry; Song, Max and Chen, William (2015) The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists Data Science Bookshelf
  • Shalev-Shwartz, Shai and Ben-David, Shai (2014) Understanding Machine Learning: From Theory to Algorithms Cambridge University Press
  • Sen, A. and M. Srivastava (2012) Regression Analysis: Theory, Methods, and Applications Springer New York
  • Peng, Roger D., Matsui, E. (2018) The Art of Data Science - A Guide for Anyone Who Works with Data PDFDRIVE
  • Lindman, H. R. (2012) Analysis of Variance in Experimental Design, 2nd ed Springer New York
  • Hastie, T., Tibshirani, R. and Friedam, J. (2009) The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed Springer-Verlag, New York
  • Faraway, J. J. (2014) Linear models with R, 2nd ed Chapman & Hall/CRC

Secundária

Não foi definida bibliografia secundária