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Product: Book - Paperback
Title: What Video Games Have to Teach Us About Learning and Literacy
Publisher: Palgrave Macmillan
Authors: James Paul Gee
Rating: 4/5
Customer opinion - 4 stars out of 5
Video Games Help Us Learn

James Paul Gee gives a different and interesting form of learning in his book. Gee shows how video games can actually help people of all ages obtain knowledge through many forms of learning. Gee argues that many schools can actually take note from video games on how to teach children and to actually hold their attention during class time. Throughout the book Gee highlights 36 learning principals that he feels video games possess and that many traditional schools should use to teach the youth of the world. According to Gee schools can learn a lot from the techniques used by video games to keep people interested in playing the same game over and over again.

One of the 36 principals that Gee represents is how video games help kids learn the use of patterns and how important they are in everyday life. Patterns help people beat video games by recognizing what methods could be useful by relating the game to parts of other video games they have played. Patterns are also present in the classroom in all subjects and Gee argues that if students could learn to recognize patterns in school material like they do in video games then students would learn the material much easier. Gee believes that schools should be responsible for helping students to recognize the patterns that exist in the material they teach.

As a teenage college student I thought the book started out a little slow. It seemed like another text book that I was forced to read for class but it quickly grabbed my attention after the second chapter. This book shows how video games are anything but a waste of time and actually can be considered to be a useful learning tool much like books. It changed my opinion on learning and teaching. I would recommend this book to anyone interested in different teaching methods or video games.

Product: Book - Paperback
Title: Gödel, Escher, Bach: An Eternal Golden Braid
Publisher: Basic Books
Authors: Douglas R. Hofstadter
Rating: 5/5
Customer opinion - 5 stars out of 5
A Wonderful Summary of the Capabilities of Spirit

Read it once, twice and trice: GEB Will surprise you again and again. In a delightful manner, Hofstadter presents us to his reach inner world, from his love to art to molecular biology and mathematical logic, all in search of the paradoxes ensuing from our recursive World.

Product: Book - Paperback
Title: Building Microsoft Access Applications
Publisher: Microsoft Press
Authors: John L. Viescas
Rating: 5/5
Customer opinion - 5 stars out of 5
Excellent Books Showing Application Development

Microsoft Access is of course a database. But it's really much more than that. With its front end forms design capability and the integral report generating system, it is well suited for quite a number of small applications. I say small, because you aren't going to use Access to handle the operations of a Fortune 500 company.

There are a lot of books that teach about the basics of Access. They however tend to talk strictly about how to do the programming portion only. They do not go into the practical aspects of database, forms, or report design.

This book takes you deeply into the design of four small and rather simple applications. This way you can see what is needed to actually make an application that is really useful. It is unlikely that you'd actually run one of these applications as is, even if they were applicable to your business, you or your boss would want something changed. But with the knowledge you would get from the rest of the book, this should be a doable task.

There is one combined plus and minus about this book. The plus, it has an excellent introduction to SQL programming, one of the best I've ever seen. The minus is that the SQL is based on the JET engine database. Access now ships with both JET and MSDE which is a much better engine. I suspect that Microsoft will make MSDE the standard engine in the future. Even with this negative, this is an excellent book.

Product: Book - Hardcover
Title: The Elements of Statistical Learning
Publisher: Springer
Authors: T. Hastie, R. Tibshirani, J. H. Friedman
Rating: 4/5
Customer opinion - 4 stars out of 5
The Elements of Statistical Learning

Data mining is a field developed by computer scientists but many of its crucial elements are imbedded in important and subtle statistical concepts. Statisticians can play an important role in the development of this field but as was the case with artificial intelligence, expert systems and neural networks the statistical research community has been slow to respond. Hastie, Tibshirani and Friedman are changing this.
Friedman has been a major player in pattern recognition of high dimensional data, in tree classification, regularized discriminant analysis and multivariate adaptive regression splines. He has also done some exciting new research on boosting methods.
Hastie and Tibshirani invented additive models which are very general types of regression models. Tibshirani invented the lasso method and is a leader among the researchers on bootstrap. Hastie invented principal curves and surfaces.
These tools and the expertise of these authors make them naturals to contribute to advances in data mining. They come with great expertise and see data mining from the statistical perspective. They see it as part of a more general process of statistical learning from data.
The book is well written and illustrated with many pretty color graphs and figures. Color adds a dimension in pattern recognition and the authors exploit it in this book. It is really the first of its kind that treats data mining from a statistical perspective and is so comprehensive and up-to-date.
The important statistical tools that are covered in this book include under the category of supervised learning; regression, discriminant analysis, kernel methods, model assessment and selection, bootstrapping, maximum likelihood and Bayesian inference, additive models, classification and regression trees, multivariate adaptive regression splines, boosting, regularization methods, nearest neighbor classification, k means clustering algorithms and neural networks. These methods are illustrated using real problems.
Similarly under the category of unsupervised learning, clustering and association are covered. They cover the latest developments in principal components and principal curves, multidimensional scaling, factor analysis and projection pursuit.
This book is innovative and fresh. It is an important contribution that will become a classic. The level is between intermediate and advanced. Good for an advanced special topics course for graduate students in statistics. The only comparable text is the text by Mannila, Hand and Smyth that I hope to be able to review in the near future.