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Introduction to the Design and Analysis of Algorithms (3rd Edition)

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Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal treatment while thoroughly covering the material required in an introductory algorithms course. Popular puzzles are used to motivate students' interest and strengthen their skills in algorithmic problem solving. Other learning-enhancement features include chapter summaries, hints to the exercises, and a detailed solution manual.
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Object Oriented Programming With C++
Object Oriented Programming With C++

The book aims at providing an all-round enrichment of knowledge in the area of object-oriented programming with C++ as the implementation of language. The author has used simple language to explain critical concepts of object-oriented programming and for...

Programming Fundamentals: A Modular Structured Approach Using C++
Programming Fundamentals: A Modular Structured Approach Using C++
The approach of this text is to take learners through a progression of materials in order to develop skills of modular, structured programming. The text was written, for the most part, without consideration of a specific programming language. However, in many cases the C++ language is discussed as part of the explanation of the concept. Often...
Graphs, Networks and Algorithms (Algorithms and Computation in Mathematics)
Graphs, Networks and Algorithms (Algorithms and Computation in Mathematics)
This new third edition has again been thoroughly revised, even though the changes are not as extensive as in the second edition. Of course, the general aims of the book have remained the same.

In particular, I have added some additional material, namely two new sections concerning graphical codes (which provides a
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Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets

As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

R and Data Mining: Examples and Case Studies
R and Data Mining: Examples and Case Studies
This book guides R users into data mining and helps data miners who use R in their work. It provides a how-to method using R for data mining applications from academia to industry. It
  • Presents an introduction into using R for data mining applications, covering most popular data mining techniques
  • ...
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