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Very interesting... this book is the volume # 31 in the series "Handbook of Statistics" edited by C.R. Rao and V. Govindaraju. The series started well before I completed my PhD in 1993, and obviously, they believe machine learning is a sub-domain of statistics. This might be the most comprehensive attempt at producing an exhaustive resource for statistician, with more than 10,000 pages to date.

Second interesting fact: I purchased the book on Amazon for less than $100, last week. Now when I check it, it is listed at $184.35. Amazon doing customized pricing? Really strange. Anyway, here's the official comments about the book:

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from physically distant locations. Recent advances made in the field of machine learning provide a strong framework for robust learning from the diverse corpora and continue to impact a variety of research problems across multiple scientific disciplines. The aim of this handbook is to familiarize beginners as well as experts with some of the recent techniques in this field.

The Handbook is divided in two sections: Theory and Applications, covering machine learning, data analytics, biometrics, document recognition and security.

  • very relevant to current research challenges faced in various fields
  • self-contained reference to machine learning
  • emphasis on applications-oriented techniques

Read details on Amazon

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