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Adam Parker
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The book opens with a great full-color photographic portrait of Grandma Moses at work at her painting table in 1952. A brief but informative biography sets the stage for the treasures that follow.
Grandma Moses was a rural New York farm wife for most of her long life, and her paintings reflect this world. Colorful, lively, and rich in detail, these paintings record and celebrate the daily lives of farm communities. We see classic farmhouses, a horse-drawn carriage, children climbing a tree, cows grazing, people engaging in chores, and other sights.
Because the book focuses on a year in Grandma's world, the paintings reflect all of the seasons. We see the green fields of springtime, the brilliant foliage of autumn, and the snowy landscapes of winter. "The Year with Grandma Moses" is a wonderful book that captures the spirit of an American creative legend.
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The first part (first seven chapters) of the book is devoted to the methods used in connectionists systems and here readers can find detailed description of the algorithms. In the second part (six chapters), which represents application of these methods, the book has a chapter devoted to the data analysis, modeling, and knowledge discovery in bioinformatics so it can be interesting for the biologists. This chapter describes how the neural network paradigm can be used in molecular biology and, in particular, for analysis in relatively new area -- microarray technology. The huge amount of data that were obtained in this area is still waiting for the efficient methods of knowledge extracting. In this chapter readers can also find the examples of using evolving connectionists learning systems for solving the problems of finding the patterns from DNA/RNA sequences, identification of intron/exon binding sites, gene profiling, protein structure prediction and dynamic cell modeling.
This excellent book is full of interesting examples, classification schemes, and figures.
Although this book will be more interesting for readers, which have been working in networking, it can be useful also for all researchers and students and any type of readers interesting in data analysis. This book is outstanding introduction for readers unfamiliar with the learning systems. The extended glossary and full-length reference list will help a lot for readers inexperienced in this area.
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The text is all here, unabridged. The image quality of the illustrations leaves a lot to be desired with this edition, however. It looks like a second-generation xerox in spots. If this is a problem, do yourself a favor and look for the 1980's hardcover reprint. The images are much better in that one. That said, the substance of this book is thoroughly recommended for the serious student of electrical engineering as well as fans of Tesla.
Since this text was written in the late 1800s, and is reprinted here without alteration, the language can sometimes have the density of Shakespeare (without the poetry). Much of the phraseology has passed out of use in the last hundred years. This material is written for the intelligencia of Tesla's era, and not "dumbed down" for this age as many other books are. This is an advantage for someone who wants an authoratative viewpoint on this subject (who more authoratative than Tesla!), but poisonous to the casual reader.
Many of the inventions discussed in this book are now commonplace (for instance - the AC induction motor, fully described here, is in use everywhere). Nikola's own depth of understanding of the principles involved make this a thoroughly intense experience for those who are ready for it. Readers who can understand this material are going to experience the devine "Ah-ha" on a regular basis throughout this book. Others will be put to sleep.
This book will separate the men from the boys very quickly.
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I also plan on purchasing XSLT Reference Guide (also by Wrox) since this book doesn't go quite as far as I'd like into XSLT.