Data Analytics - Machine Learning

Contents

    • Day1:
    • Day2:


Books, Articles, Blogs and Learning Resources:

  1. Introduction to Machine Learning, 2nd Edition by Ethem Alpaydın. URL
  2. A Course in Machine Learning by Hal Daumé III. URL
  3. Machine Learning in Action by Peter Harrington. URL
  4. Introduction to Machine Learning by Alex Smola and S.V.N. Vishwanathan. URL
  5. Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz and Shai Ben-David. URL
  6. Must Read Books for Beginners on Machine Learning and Artificial Intelligence. URL
  7. Introduction to Machine Learning (An Early Draft of A Proposed Textbook) by Nils J. Nilsson. URL
  8. Book:Machine Learning – The Complete Guide. URL
  9. Information Theory, Inference, and Learning Algorithms by David J.C. MacKay. URL
  10. Machine Learning A Probabilistic Perspective by Kevin P. Murphy. URL
  11. 35 Free Online Books on Machine Learning. URL
  12. Machine Learning by Tom M. Mitchell. URL; Machine Learning, Tom Mitchell, McGraw-Hill. (Slides for instructors). URL
  13. Machine Learning Tutorial by Wei-Lun Chao. URL
  14. Machine Learning, Neural and Statistical Classification (Editors: D. Michie, D.J. Spiegelhalter, C.C. Taylor). URL
  15. Gaussian Processes for Machine Learning by Carl Edward Rasmussen & Christopher K. I. Williams. URL
  16. An Introduction to Statistical Learning with Applications in R (Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani). URL
  17. Building Machine Learning Systems with Python by Willi Richert & Luis Pedro Coelho. URL
  18. An Introduction to Statistical Learning with Applications in R (Gareth James, Daniela Witten, Trevor Hastie & Robert Tibshirani). URL
  19. DSO 530: Applied Modern Statistical Learning Techniques (Abbass Al Sharif, Assistant Professor of Clinical Data Sciences). URL
  20. Introduction to Statistical Machine Learning by Masashi Sugiyama (ISBN: 978-0-12-802121-7). URL
  21. Machine Learning: Making Sense of Data by Peter Flach. URL
  22. Books on Adaptive Computation and Machine Learning (MIT Press). URL
  23. 60+ Free Books on Big Data, Data Science, Data Mining, Machine Learning, Python, R, and more. URL
  24. A Few Useful Things to Know about Machine Learning by Pedro Domingos. URL
  25. A First Encounter with Machine Learning by Max Welling. URL
  26. 27 Free Data Mining Books. URL
  27. Bayesian Reasoning and Machine Learning by David Barber. URL
  28. Machine Learning in Computer Vision by N. Sebe, Ira Cohen, Ashutosh Garg, & Thomas S. Huang. URL
  29. Python Machine Learning by Sebastian Raschka. URL
  30. Machine Learning Engineer Nanodegree. URL
  31. Computer Vision: Models, Learning, and Inference by Simon J.D. Prince. URL
  32. Christopher Bishop, Laboratory Director, Microsoft Research Cambridge. URL
  33. Introduction to Machine Learning, second edition by Ethem Alpaydin. URL
  34. List of 35 Free eBooks on Machine Learning & Related Fields. URL
  35. D. Chen and P. Burrell, 'Case-based reasoning system and artificial neural networks: A Review (pdf file)', in Neural Computing & Applications, vol. 10, no. 3, pp. 264-276, 2001 (Copyright 2001 Springer). URL
  36. M.F. Valstar and M. Pantic, 'Biologically vs. logic inspired encoding of facial actions and emotions in video (pdf file)', in Proc. IEEE Int'l Conf. on Multimedia and Expo (ICME '06), Toronto, Canada, July 2006 (Copyright 2006 IEEE Press). URL
  37. S. Petridis and M. Pantic, 'Audiovisual Discrimination between Laughter and Speech (pdf file)', in Proc. IEEE Int’l Conf. Acoustics, Speech and Signal Processing (ICASSP’08), pp. 5117-5120, Las Vegas, USA, April 2008 (Copyright © 2008 IEEE Press). URL
  38. A Short History of Machine Learning -- Every Manager Should Read. URL1; URL2
  39. Alan Turing Predicts Machine Learning And The Impact Of Artificial Intelligence On Jobs. URL1; URL2

Useful Links & Resources:

  1. Machine Learning with Matlab. URL1; Section-1: URL2; Section-2: URL3; Section-3: URL4; Section-4: URL5
  2. Supervised Learning Workflow and Algorithms. URL
  3. The Classification Learner. URL
  4. Classification Examples. URL
  5. Data-Driven Insights with MATLAB Analytics: An Energy Load Forecasting Case Study. URL
  6. Machine Learning Made Easy (Shashank Prasanna, MathWorks). URL
  7. Signal Processing and Machine Learning Techniques for Sensor Data Analytics (Gabriele Bunkheila, MathWorks). URL
  8. Signal Processing Toolbox (Perform signal processing and analysis). URL