Machine Learning

  • My profile on Kaggle.com
  • R Slidify presentation "Machine Learning: basics and case studies" for students
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    Time series forecasting

  • "Forecasting: principles and practice", online book by Rob Hyndman and George Athanasopoulos
    This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

    • Bayesian methods

  • Bayesian Model Averaging
  • Tim Salimans home page
    Very nice explanation of Bayesian approach for some Machine Learning problems

    • Software

  • R language + R Studio IDE
  • Python + Machine Learning package SciKit
  • Julia language + Julia Studio IDE
  • MATLAB
  • Factorization Machine Library by Steffen Rendle
  • Library of learning to rank algorithms RankLib
  • Toolbox for large scale kernel methods Shogun
  • Support vector machine for ranking SVMrank
  • Learning algorithms from Yahoo! Research Vowpal Wabbit
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