Read Principles and Theory for Data Mining and Machine Learning (Springer Series in Statistics) by Bertrand Clarke, Ernest Fokoue, Hao Helen Zhang Online
Read ^ Principles and Theory for Data Mining and Machine Learning (Springer Series in Statistics) PDF by * Bertrand Clarke, Ernest Fokoue, Hao Helen Zhang eBook or Kindle ePUB Online free. Principles and Theory for Data Mining and Machine Learning (Springer Series in Statistics) Extensive treatment of the most up-to-date topicsProvides the theory and concepts behind popular and emerging methodsRange of topics drawn from Statistics, Computer Science, and Electrical Engineering]
| Title | : | Principles and Theory for Data Mining and Machine Learning (Springer Series in Statistics) |
| Author | : | |
| Rating | : | 4.24 (623 Votes) |
| Asin | : | 0387981349 |
| Format Type | : | paperback |
| Number of Pages | : | 786 Pages |
| Publish Date | : | 2014-07-29 |
| Language | : | English |
An overall good book, although a hard one. This book covers many methods in data mining and machine learning. The best thing to me is that it tells each story from a theoretical way, but not a superficial way. It really helps you understand these machine learning methods from a deep perspective. Reading this book did let me think more thoroughly. Of course the good thing can be a bad thing in that, if you do not have enough background in statistics and math, this book can be very difficult to read. The famous Hastie, Tibshirani and Friedma
… The over-riding reason for staying with the independent, symmetric unimodal error model is surely that no one book can cover everything! Within these bounds, this book gives a careful treatment that is encyclopedic in its scope.” (John H. … the authors have done an outstanding job of covering important topics and providing relevant statistical theory and computational resources. Computed examples that include R code are scattered through the text. Maindonald, International Statistical Review, Vol. 79 (1), 2011)“It is an appropriate textbook for a PhD level course and can also be used as a reference or for independent reading. … A s
Extensive treatment of the most up-to-date topicsProvides the theory and concepts behind popular and emerging methodsRange of topics drawn from Statistics, Computer Science, and Electrical Engineering
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