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Readings in Machine Learning (The Morgan Kaufmann Series in Machine Learning)

Readings in Machine Learning (The Morgan Kaufmann Series in Machine Learning)

List Price: $73.95
Your Price: $73.95
Product Info Reviews

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Rating: 5 stars
Summary: Absolute must for any work in the field.
Review: The aim of the book is to bring together key papers in Machine Learning and to provide an introduction to the field and a reference collection for graduate students and researchers. The book contains 51 most imoportant article from Machine Learning (up to 1990). Most of these are NOT available online, so watch out! The following areas are covered: Introduction (3 papers; one by Simon), Inductive Learning From Preclassified Training Examples (16 papers including great classics from Quinlan, Michalski, Mitchell, Minsky...), Unsupervided Learning and Concept Discovery (9 papers -- Feigenbaum, Holland...), Improving the Efiiciency of a Problem Solver (10 papers including fameous Samuel's gem "Some Studies in Machine Learning Using the Game of Checkers"; also papers from Mitchell, Nillson, Utgoff...), Using Preexisting Domain Knowledge Inductively (13 papers; Russel, etc...). Really really outstanding collection and a definite recommendation.

Rating: 5 stars
Summary: Absolute must for any work in the field.
Review: The aim of the book is to bring together key papers in Machine Learning and to provide an introduction to the field and a reference collection for graduate students and researchers. The book contains 51 most imoportant article from Machine Learning (up to 1990). Most of these are NOT available online, so watch out! The following areas are covered: Introduction (3 papers; one by Simon), Inductive Learning From Preclassified Training Examples (16 papers including great classics from Quinlan, Michalski, Mitchell, Minsky...), Unsupervided Learning and Concept Discovery (9 papers -- Feigenbaum, Holland...), Improving the Efiiciency of a Problem Solver (10 papers including fameous Samuel's gem "Some Studies in Machine Learning Using the Game of Checkers"; also papers from Mitchell, Nillson, Utgoff...), Using Preexisting Domain Knowledge Inductively (13 papers; Russel, etc...). Really really outstanding collection and a definite recommendation.


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