[1]
Abu-Mostafa, Y.S. et al. 2012. Learning from data: a short course. AMLBook.com.
[2]
Barber, D. 2012. Bayesian reasoning and machine learning. Cambridge University Press.
[3]
Bishop, C.M. 2006. Pattern recognition and machine learning. Springer.
[4]
Casella, G. and Berger, R.L. 2017. Statistical inference. Cengage Learning.
[5]
Goodfellow, I. et al. 2016. Deep learning. The MIT Press.
[6]
Grimmett, G. and Stirzaker, D. 2001. Probability and random processes. Oxford University Press.
[7]
Harrington, P. 2012. Machine learning in action. Manning Publications.
[8]
Hastie, T. et al. 2009. The elements of statistical learning: data mining, inference, and prediction. Springer.
[9]
Hastie, T. et al. 2001. The elements of statistical learning: data mining, inference, and prediction : with 200 full-color illustrations. Springer.
[10]
Kabacoff, R. 2015. R in action: data analysis and graphics with R. Manning.
[11]
Karau, H. et al. 2013. Learning Spark: lightning-fast big data analytics. O’Reilly.
[12]
Kevin Sheppard - Lecture Notes: https://www.kevinsheppard.com/Main_Page.
[13]
Kiusalaas, J. 2016. Numerical methods in engineering with MATLAB. Cambridge University Press.
[14]
Lantz, B. 2013. Machine learning with R: learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications. Packt Publishing Limited.
[15]
Martinez, W.L. and Martinez, A.R. 2016. Computational statistics handbook with MATLAB. Chapman & Hall/CRC.
[16]
McKinney, W. 2013. Python for data analysis. O’Reilly.
[17]
Mood, A.M. et al. 1974. Introduction to the theory of statistics. McGraw-Hill Book Company.
[18]
Murphy, K.P. 2012. Machine learning: a probabilistic perspective. MIT Press.
[19]
Nolan, D.A. and Lang, D.T. eds. 2015. Data science in R: a case studies approach to computational reasoning and problem solving. Chapman & Hall/CRC.
[20]
Peng, R. 2016. R Programming for Data Science. Lulu.com.
[21]
Raschka, S. 2015. Python machine learning: unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics. Packt Publishing.
[22]
Sarkar, D. 2008. Lattice: multivariate data visualization with R. Springer.
[23]
Source Code for the book: Machine Learning in Action published by Manning: https://github.com/pbharrin/machinelearninginaction.
[24]
Wickham, H. 2014. Advanced R. Chapman & Hall/CRC.
[25]
Wickham, H. 2014. Advanced R. Chapman & Hall/CRC.
[26]
Wickham, H. 2009. ggplot2: elegant graphics for data analysis. Springer.
[27]
Wickham, H. 2015. R packages. O’Reilly Media.
[28]
Zumel, N. and Mount, J. 2014. Practical data science with R. Manning.