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Product: Book - Paperback
Title: Hacker Disassembling Uncovered
Publisher: A-List Publishing
Authors: Kris Kaspersky
Rating: 5/5
Customer opinion - 5 stars out of 5
Just use it


First the good news: Very few books give a total picture of assembler code. Usually they are text books, but this is a real hands on book to learn lot of assembler structures. How does a programs laid out(executible file format), what library functions get statically linked, and how they are resolved, how does relocation works, how does loader loads etc., etc. You would find a long lasting knowledge from this book. IF YOU ARE A SYSTEM AND/OR KERNEL MODE PROGRAMMER, IT IS A MUST. But need to go thru the exercises...
Bad news is that it seems like the examples are not tried out with MS visual studio 6.0. You will find the code generation is different, due to some inline library code (ie, strcmp() and others). It does have other mistakes in the programming, as well as in the text. Stack based code execution at the end of the book does not seem to do its job.
But still it is an excellent book to read and go thru those examples to become fairly fluent with large assembler codes, and their working. WHEN THE INFORMATION BASE IS HUGE, LOOK FOR STRUCTURE, AVOID THE DETAIL UNTIL NEEDED, this is precisely this book follows. Nothing could be worse than ignorance, so go grab one !!!



Product: Book - Paperback
Title: Java 2: The Complete Reference, Fifth Edition
Publisher: McGraw-Hill Osborne Media
Authors: Herbert Schildt
Rating: 5/5
Customer opinion - 5 stars out of 5
A Great Reference for Novice & Experienced Programmers Alike


When I needed to learn the Java programming language very quickly for work, I read many reviews and narrowed down my search to handful of few books. I looked at copies of my final possible choices in a local bookstore and finally purchased Herbert Schildt's "Java 2: A Beginner's Guide, Second Edition" and have absolutely no regrets. Along with this book, I realized that I would also need a more comprehensive reference book detailing the multitude of Java classes designed for many purposes. To this end, I chose Herbert Schildt's "Java 2: The Complete Reference, Fifth Edition" not only for its extensive library, but also because of Herbert Schildt's wonderful writing that is easy to read and understand quickly.
Herbert Schildt subdivided "Java 2: The Complete Reference, Fifth Edition" into four parts: tutorial, library, software development and applications. Part I (the first 346 pages) is a Java tutorial, organized similarly to Herbert Schildt's other book that I purchased, "Java 2: A Beginner's Guide, Second Edition". However, the tutorial in this book is more condensed than in the guide, which has over 500 pages. Some readers may find the condensed approach in this book sufficient to learn the language, but if you want more comprehensive tutorial explanations, the guide is good companion.
Part II (the next 539 pages) is an extensive library detailing most of Java's built-in classes dealing with everything from string handling, collections, utility classes, console I/O, file I/O, networking, applets, event handling (mouse movements, button use, and other interactive GUI objects), the AWT (Abstract Window Toolkit), images and other I/O types including Regular Expressions. Part III (the next 128 pages) provides some information about Java Beans, Swing, Servlets and a helpful guide for migrating from C++ to Java. Part IV (the next 123 pages) shows Java in action with four example applications.
Overall, I rate Herbert Schildt's "Java 2: The Complete Reference, Fifth Edition" with 5 out of 5 stars. It has become a constant companion as I learn and work with Java.



Product: Book - Hardcover
Title: Principles of Data Mining (Adaptive Computation and Machine Learning)
Publisher: The MIT Press
Authors: David J. Hand, Heikki Mannila, Padhraic Smyth
Rating: 5/5
Customer opinion - 5 stars out of 5
nice treatment of data mining and underlying methodology


This book is not an introductory text. Anyone interested in a particular topic should consult the preface of the text to find out what it is about. The negative reviewers were not fair to the authors on that score. Had they read the preface they would have found out (1) how the authors define data mining, (2) that they see it as a subject with an important mix of statistical methodology and computer science and (3) that it is intended as an advanced undergraduate or first year graduate text on the topic.
They also provide a very well organized structure for the text that is well described in the preface. It consists of three parts. Chapter 1 is an essential introduction that is informative to everyone. Chapters 2 through 4 go through basic statistical ideas that statisticians would be very familiar with and others could view as a refresher. The authors have experience teaching this course to engineering and science majors and have found that many of these students unfortunately do not have the prerequisite statistical inference ideas and need this material covered in the course.
Chapters 5 through 8 cover the components of data mining algorithms and the remaining chapters deal with the details of the tasks and algorithms.
The book features a further reading section at the end of each chapter that provides a very nice guide to the useful and most significant relevant literature. The author's have done a very good job at this. One mistake I found was a reference to Miller (1980). I think this was intended to be a reference to the seocnd edition fo Rupert Miller's text "Simultaneous Statistical Inference" which was published in 1981 by Springer-Verlag but the full citation is missing from the list of references in the back of the book.
This book deserves 5 stars because it does what it intends to do. It presents the field of data mining in a clear way covering topics on classfication and kernel methods expertly. David Hand has published a great deal on these techniques including many fine books. Mannila and Smyth bring to the text the computer science perspective. There is much useful material on optimization methods and computational complexity.
Statistical modeling and issues of the "curse of dimensionality" and the "overfitting problem" are key issues that this text emphasizes and expertly addresses.
The only thing the text misses is details on specific algorithms. But I do not grade them down for that because it was not their intention. They emphasize methodology and issues and that is the most critical thing a practitioner needs to know first before embarking on his own attack at mining data.
The text does provide most of the current important methods. Although Vapnik's work is mentioned and his two books are referenced there is very little discussion of support vector machines and the use of Vapnik-Chervonenkis classes and dimensionin data mining. The new book by Hastie, Tibshirani and Friedman goes into much greater detail on specific algorithms include some only briefly discussed in this text (e.g. support vector machines). The support vector approach is also nicely treated in "Learning with Kernels" by Scholkopf and Smola.
I highly recommend this book for anyone interested in data mining. It is a great reference source and an eloquent text to remind you of the pitfalls of thoughtless mining or "data-dredging". It also has many nice practical examples and some interesting success stories on the application of data mining to specific problems.



Product: Book - Paperback
Title: Enterprise JavaBeans, Fourth Edition
Publisher: O'Reilly
Authors: Richard Monson-Haefel, Bill Burke, Sacha Labourey
Rating: 2/5
Customer opinion - 2 stars out of 5
A mediocre introduction to EJB


Upon first reading this book, I didn't know to think little of it. Then I took reading other EJB books and found this one wanting for the following reasons: Entity Beans are described prior to describing Session Beans (when Entity Beans can be likened to specialized Stateful Session Beans), at no time did the book clearly and concisely state the bare minimum necessary to implement a Entity and Session Beans, and the book seemed to assume prior knowledge of other Java technologies such as JNDI and RMI.
As I stated above, there are other books out there (that I will not name as I believe that I had a review censored for naming a book) that more clearly delineate what an EJB developer needs to know to hit the ground running. Look elsewhere.