APAR
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  • Classes Material
    • Introduction
    • Reporting
    • Predictive Analytics
    • Data Pre-processing
    • Performance Estimation
    • Stock Market Case Study
  • Bibliography
  • Contact

Bibliography

  • Books
    • Recommended for the subject
      • Charu C. Aggarwal (2015): Data Mining, the textbook. Springer.
      • Torgo, L. (2017): Data Mining with R, learning with case studies, 2nd edition. CRC Press.
        supporting material to the book
      • J. Han , M. Kamber and J. Pei (2011): Data Mining - Concepts and Techniques (3rd edition). ISBN: 9780123814791
    • Other extra books
      • B. S. Baumer, D. T. Kaplan and N. J. Horton (2017): Modern Data Science with R. CRC Press.
      • Peter Flach (2012): Machine Learning, Cambridge University Press. ISBN: 978-1-107-42222-3
      • Kuhn,M. and Johnson,K. (2013): Applied Predictive Modeling. Springer.
      • Chambers, J. (2008): Software for Data Analysis, programming in R. Springer.
      • Adler, J. (2010): R in a nutshell. O’Reilly.
    • Free/web-based books
      • Wickham,H. (2014): Advanced R. The R Series. CRC Press.
        Free web access
      • Grolemund, G. ; Wickham, H. (2016): R for Data Science. O’Reilly.
        Free web access
      • Peng, R. (2016): R Programming for Data Science.
      • Several free R books