Showing posts with label Computer Application. Show all posts
Showing posts with label Computer Application. Show all posts
Monday, December 28, 2009
The Adobe Photoshop Lightroom 2 Book for Digital Photographers
Product Description
Written in concert with Adobe's development of the Photoshop Lightroom 2 Beta, The Adobe Photoshop Lightroom 2 Book for Digital Photographers - by #1 bestselling computer and technology author, Scott Kelby - is the most complete and concise Lightroom "how-to" book for digital photographers of all skill levels.
In The Adobe Photoshop Lightroom 2 Book for Digital Photographers, Scott walks readers through the basics of Lightroom use, leading them to a brilliantly devised and super efficient digital photography workflow that dramatically improves productivity and allows photographers to spend less time processing photos and more time shooting them.
Throughout the book Scott shares his personal camera and Lightroom settings, as well as the studio-tested techniques he's developed for his own photography workflow. The book is written in his trademark step-by-step, plain English style, and because he knows what really works and what doesn't, he isn't shy to tell you flat out which tools to use, which to avoid, and why. This allows digital photographers of any skill level to jump right in using Lightroom like a pro from the very start, sidestepping a lot of the frustrations that typically haunt those unfamiliar with new applications…especially those as powerful as Lightroom.
What really sets The Adobe Photoshop Lightroom 2 Book for Digital Photographers apart from other Lightroom books on the market are the last two bonus chapters where Scott answers the questions, "In exactly what order am I supposed to do things in Lightoom," and "Where does Photoshop fit in to the mix?" Both chapters start with an on-location photo shoot, including full details on the equipment, camera settings, and lighting techniques. Readers then witness as he takes the photos from each shoot through the entire workflow process, to the final output of the 16"x20" prints. And, because he incorporates Photoshop seamlessly right into this workflow, you'll learn some of the latest Photoshop techniques for portrait and landscape photography as well.
If you're one of those people who learns best by actually doing the projects yourself; who learns best without all the complicated technical explanations and confusing jargon, and if you really want to start using Lightroom today to unlock the productivity secrets of "The new digital photography workflow,"---there is no faster, more "straight-to-the-point" or more fun way to learn than this groundbreaking new book, and you are absolutely going to love it!
Coders at Work
Product Description
Peter Seibel interviews 15 of the most interesting computer programmers alive today in Coders at Work, offering a brand-new companion volume to Apress’s highly acclaimed best-seller Founders at Work by Jessica Livingston. As the words “at work” suggest, Peter Seibel focuses on how his interviewees tackle the day-to-day work of programming, while revealing much more, like how they became great programmers, how they recognize programming talent in others, and what kinds of problems they find most interesting.
Hundreds of people have suggested names of programmers to interview on the Coders at Work web site: www.codersatwork.com. The complete list was 284 names. Having digested everyone’s feedback, we selected 15 folks who’ve been kind enough to agree to be interviewed:
* Frances Allen: Pioneer in optimizing compilers, first woman to win the Turing Award (2006) and first female IBM fellow
* Joe Armstrong: Inventor of Erlang
* Joshua Bloch: Author of the Java collections framework, now at Google
* Bernie Cosell: One of the main software guys behind the original ARPANET IMPs and a master debugger
* Douglas Crockford: JSON founder, JavaScript architect at Yahoo!
* L. Peter Deutsch: Author of Ghostscript, implementer of Smalltalk-80 at Xerox PARC and Lisp 1.5 on PDP-1
* Brendan Eich: Inventor of JavaScript, CTO of the Mozilla Corporation
* Brad Fitzpatrick: Writer of LiveJournal, OpenID, memcached, and Perlbal
* Dan Ingalls: Smalltalk implementor and designer
* Simon Peyton Jones: Coinventor of Haskell and lead designer of Glasgow Haskell Compiler
* Donald Knuth: Author of The Art of Computer Programming and creator of TeX
* Peter Norvig: Director of Research at Google and author of the standard text on AI
* Guy Steele: Coinventor of Scheme and part of the Common Lisp Gang of Five, currently working on Fortress
* Ken Thompson: Inventor of UNIX
* Jamie Zawinski: Author of XEmacs and early Netscape/Mozilla hacker
What you’ll learn
How the best programmers in the world do their job
Who is this book for?
Programmers interested in the point of view of leaders in the field. Programmers looking for approaches that work for some of these outstanding programmers.
About the Author
Peter Seibel is a serious developer of long standing. In the early days of the Web, he hacked Perl for Mother Jones Magazine and Organic Online. He participated in the Java revolution as an early employee at WebLogic which, after its acquisition by BEA, became the cornerstone of the latter’s rapid growth in the J2EE sphere. He has also taught Java programming at UC Berkeley Extension. He is the author of Practical Common LISP from Apress.
Excel 2007 Bible
Product Description
* This book is a single reference that’s indispensable for Excel beginners, intermediate users, power users, and would-be power users everywhere
* Fully updated for the new release, this latest edition provides comprehensive, soup-to-nuts coverage, delivering over 900 pages of Excel tips, tricks, and techniques readers won’t find anywhere else
* John Walkenbach, aka "Mr. Spreadsheet," is one of the liworld’s leading authorities on Excel
* Thoroughly updated to cover the revamped Excel interface, new file formats, enhanced interactivity with other Office applications, and upgraded collaboration features
* Includes a valuable CD-ROM with templates and worksheets from the book
Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
About the Author
John Walkenbach, a.k.a "Mr. Spreadsheet," is a principal of J-Walk and Associates, Inc. and a Microsoft Excel MVP. He is a leading authority on spreadsheet software and creator of the award-winning Power Utility Pak. He has written more than 50 books, including Excel 2003 Formulas and Excel 2003 Power Programming with VBA, as well as articles and reviews for publications including PC World, InfoWorld, and Windows. He also maintains the popular Spreadsheet Page at www.j-walk.com/ss.
Head First Java, 2nd Edition
Product Description
Learning a complex new language is no easy task especially when it s an object-oriented computer programming language like Java. You might think the problem is your brain. It seems to have a mind of its own, a mind that doesn't always want to take in the dry, technical stuff you're forced to study.
The fact is your brain craves novelty. It's constantly searching, scanning, waiting for something unusual to happen. After all, that's the way it was built to help you stay alive. It takes all the routine, ordinary, dull stuff and filters it to the background so it won't interfere with your brain's real work--recording things that matter. How does your brain know what matters? It's like the creators of the Head First approach say, suppose you're out for a hike and a tiger jumps in front of you, what happens in your brain? Neurons fire. Emotions crank up. Chemicals surge.
That's how your brain knows.
And that's how your brain will learn Java. Head First Java combines puzzles, strong visuals, mysteries, and soul-searching interviews with famous Java objects to engage you in many different ways. It's fast, it's fun, and its effective. And, despite its playful appearance, Head First Java is serious stuff: a complete introduction to object-oriented programming and Java. You'll learn everything from the fundamentals to advanced topics, including threads, network sockets, and distributed programming with RMI. And the new. second edition focuses on Java 5.0, the latest version of the Java language and development platform. Because Java 5.0 is a major update to the platform, with deep, code-level changes, even more careful study and implementation is required. So learning the Head First way is more important than ever.
If you've read a Head First book, you know what to expect--a visually rich format designed for the way your brain works. If you haven't, you're in for a treat. You'll see why people say it's unlike any other Java book you've ever read.
By exploiting how your brain works, Head First Java compresses the time it takes to learn and retain--complex information. Its unique approach not only shows you what you need to know about Java syntax, it teaches you to think like a Java programmer. If you want to be bored, buy some other book. But if you want to understand Java, this book's for you.
About the Author
Kathy Sierra is a co-developer of the SCJP exam and Sun's practice exam. She is also a Sun Certified Java Instructor and the founder of the world's largest Java certification website, Javaranch.com.Bert Bates is a Sun Certified Programmer for Java and has participated in the development of the SCJP exam and Sun's practice exam. He is the coauthor, with Kathy Sierra, of the previous editions of this book.
Friday, October 10, 2008
Data Analysis Using SQL and Excel
Product Description
Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like.
Product Details
* Amazon Sales Rank: #53470 in Books
* Published on: 2007-10-01
* Original language: English
* Number of items: 1
* Binding: Paperback
* 645 pages
Editorial Reviews
From the Back Cover
Leverage the power of SQL and Excel to perform business analysis
Three key efforts are essential to effectively transform data into actionable information: retrieving data with SQL, presenting data with Excel, and understanding statistics as the foundation of data analysis. Data mining expert Gordon Linoff focuses on these topics and shows you how SQL and Excel can be used to extract business information from relational databases. He begins by taking a look at how data is central to the task of understanding customers, products, and markets, and he then goes on to show you how to use that data to define business dimensions, store transactions about customers, and summarize important data to produce results. Along the way, he shares stories based on his personal experience in the field, intended to enrich your understanding of why some things work—and others don't.
Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what you can expect the results to look like. Throughout the book, critical features of Excel are highlighted, interesting uses of Excel graphics are explained, and dataflows and graphical representations of data processing are used to illustrate how SQL works.
Data Analysis Using SQL and Excel shares hints, warnings, and technical asides about Excel, SQL, and data analysis/mining. The book also discusses:
* How entity-relationship diagrams describe the structure of data
*
Ways to use SQL to generate SQL queries
*
Descriptive statistics, such as averages, p-values, and the chi-square test
*
How to incorporate geographic information into data analysis
*
Basic ideas of hazard probabilities and survival
*
How data structures summarize what a customer looks like at a specific point in time
*
Several variants of linear regression
The companion Web site provides the data sets, Excel spreadsheets, and examples featured in the book.
About the Author
GORDON S. LINOFF is a cofounder of Data Miners, Inc., a consultancy specializing in data mining. He is the coauthor of the bestselling Data Mining Techniques, Second Edition, and Mastering Data Mining (both from Wiley). He has more than a decade of experience applying data mining techniques to business problems in marketing and customer relationship management.
Customer Reviews
At last .. a practical data analysis guide!5
Having seen a multitude of books offering either statistical analysis techniques or suggestions around data mining tools, it is refreshing to see someone approach the subject using simple, readily available tools and a practical, business oriented approach to the topic. The apparently mundane subject of customer retention coupled with buying patterns and market basket analysis is laid out in an effective and sequential manner. The SQL examples take some getting used to but, once understood, offer a series of easily implemented and highly effective methods to illustrate the concepts shown in the book. As a reference guide and an illustration that one needs to know the questions to be asked of the data before investing in the latest drag and drop business intelligence tools, this book is unparalleled. The author has not stinted on providing a wealth of examples and explanation. If this tome is a reflection of how Mr Linoff and his team approach their real world consulting activities, they must be a formidable team indeed.
For anyone who has wrestled with a means to understand their customer buying patterns and product affinity patterns in their historical sales data, this book cannot be beaten
Review from a non-statistician and business intelligence manager5
"Data Analysis Using SQL and Excel" is an valuable resource for business intelligence and data mining practitioners in all industries. Having said that, I would like to offer some solid practical advice to potential readers that might not be fluent in statistics or data mining.
First, the reader should have a solid understanding of SQL. If the extent of your SQL interaction comes through a program on the level of Access, then you can still benefit from this book, but you will have to apply yourself more than others. Keep in mind, that proprietary releases of SQL might cause problems in directly translating the author's examples.
Second, if your statistics knowledge is a little rusty, have a secondary resource on-hand. Sometimes the definitions or explanations of the statistical concepts may not be as intuitive for some readers as they are for others.
With those caveats in mind, the reader need only to keep his or her patience and work through the concepts of the first 4-5 chapters. These chapters tend toward simple exposition of the concepts. For those with little patience, it may seem as if it is just a laundry list of concepts with little effort to tie those concepts into practical uses. Thinking like this is a great way to miss the enormous benefits of the book!
For me, the "Ah Ha!" moment came in Chapter 6 and 7. The concepts I had worked on in the previous chapters suddenly came together with customer tenure onward, when the techniques use will call to mind everything learned in the previous chapters.
In short, spend plenty of time in the first few chapters - the extra effort to master those concepts will only enhance the benefits of later chapters.
Lastly, there are a few odd differences between the text and the files downloadable from the web site. Whenever I hit a snag based on the text, opening the accompanying Excel files and seeing the formulas, queries or table/graph structures resolved all issues for me.
This is a text that will always have a place on my shelves.
A wonderful mix of theory and practice5
If you work, like me, on data warehousing, data mining, analytical CRM or similar projects, this book will save you a lot of time, and provide you with a lot of inspiration.
Statistical concepts are clearly explained, and examples with very smart SQL queries and Excel sheets are shown.
For instance, no other book will explain you so clearly Survival Analysis, and how to practically implement it (I mean, with working code!).
As a previous reviewer wrote, why should you believe me? I'm one of the authors of another Wiley book, "MDX Solutions", and I earn my living by consulting with DaisyLabs, a Business Intelligence company.
Keep Gordon's book on SQL, and my book on MDX, on your desk, and no data analysis project will scare you anymore!
Useful business analysis requires you to effectively transform data into actionable information. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what the results should look like.
Product Details
* Amazon Sales Rank: #53470 in Books
* Published on: 2007-10-01
* Original language: English
* Number of items: 1
* Binding: Paperback
* 645 pages
Editorial Reviews
From the Back Cover
Leverage the power of SQL and Excel to perform business analysis
Three key efforts are essential to effectively transform data into actionable information: retrieving data with SQL, presenting data with Excel, and understanding statistics as the foundation of data analysis. Data mining expert Gordon Linoff focuses on these topics and shows you how SQL and Excel can be used to extract business information from relational databases. He begins by taking a look at how data is central to the task of understanding customers, products, and markets, and he then goes on to show you how to use that data to define business dimensions, store transactions about customers, and summarize important data to produce results. Along the way, he shares stories based on his personal experience in the field, intended to enrich your understanding of why some things work—and others don't.
Each chapter explains when and why to perform a particular type of business analysis in order to obtain useful results, how to design and perform the analysis using SQL and Excel, and what you can expect the results to look like. Throughout the book, critical features of Excel are highlighted, interesting uses of Excel graphics are explained, and dataflows and graphical representations of data processing are used to illustrate how SQL works.
Data Analysis Using SQL and Excel shares hints, warnings, and technical asides about Excel, SQL, and data analysis/mining. The book also discusses:
* How entity-relationship diagrams describe the structure of data
*
Ways to use SQL to generate SQL queries
*
Descriptive statistics, such as averages, p-values, and the chi-square test
*
How to incorporate geographic information into data analysis
*
Basic ideas of hazard probabilities and survival
*
How data structures summarize what a customer looks like at a specific point in time
*
Several variants of linear regression
The companion Web site provides the data sets, Excel spreadsheets, and examples featured in the book.
About the Author
GORDON S. LINOFF is a cofounder of Data Miners, Inc., a consultancy specializing in data mining. He is the coauthor of the bestselling Data Mining Techniques, Second Edition, and Mastering Data Mining (both from Wiley). He has more than a decade of experience applying data mining techniques to business problems in marketing and customer relationship management.
Customer Reviews
At last .. a practical data analysis guide!5
Having seen a multitude of books offering either statistical analysis techniques or suggestions around data mining tools, it is refreshing to see someone approach the subject using simple, readily available tools and a practical, business oriented approach to the topic. The apparently mundane subject of customer retention coupled with buying patterns and market basket analysis is laid out in an effective and sequential manner. The SQL examples take some getting used to but, once understood, offer a series of easily implemented and highly effective methods to illustrate the concepts shown in the book. As a reference guide and an illustration that one needs to know the questions to be asked of the data before investing in the latest drag and drop business intelligence tools, this book is unparalleled. The author has not stinted on providing a wealth of examples and explanation. If this tome is a reflection of how Mr Linoff and his team approach their real world consulting activities, they must be a formidable team indeed.
For anyone who has wrestled with a means to understand their customer buying patterns and product affinity patterns in their historical sales data, this book cannot be beaten
Review from a non-statistician and business intelligence manager5
"Data Analysis Using SQL and Excel" is an valuable resource for business intelligence and data mining practitioners in all industries. Having said that, I would like to offer some solid practical advice to potential readers that might not be fluent in statistics or data mining.
First, the reader should have a solid understanding of SQL. If the extent of your SQL interaction comes through a program on the level of Access, then you can still benefit from this book, but you will have to apply yourself more than others. Keep in mind, that proprietary releases of SQL might cause problems in directly translating the author's examples.
Second, if your statistics knowledge is a little rusty, have a secondary resource on-hand. Sometimes the definitions or explanations of the statistical concepts may not be as intuitive for some readers as they are for others.
With those caveats in mind, the reader need only to keep his or her patience and work through the concepts of the first 4-5 chapters. These chapters tend toward simple exposition of the concepts. For those with little patience, it may seem as if it is just a laundry list of concepts with little effort to tie those concepts into practical uses. Thinking like this is a great way to miss the enormous benefits of the book!
For me, the "Ah Ha!" moment came in Chapter 6 and 7. The concepts I had worked on in the previous chapters suddenly came together with customer tenure onward, when the techniques use will call to mind everything learned in the previous chapters.
In short, spend plenty of time in the first few chapters - the extra effort to master those concepts will only enhance the benefits of later chapters.
Lastly, there are a few odd differences between the text and the files downloadable from the web site. Whenever I hit a snag based on the text, opening the accompanying Excel files and seeing the formulas, queries or table/graph structures resolved all issues for me.
This is a text that will always have a place on my shelves.
A wonderful mix of theory and practice5
If you work, like me, on data warehousing, data mining, analytical CRM or similar projects, this book will save you a lot of time, and provide you with a lot of inspiration.
Statistical concepts are clearly explained, and examples with very smart SQL queries and Excel sheets are shown.
For instance, no other book will explain you so clearly Survival Analysis, and how to practically implement it (I mean, with working code!).
As a previous reviewer wrote, why should you believe me? I'm one of the authors of another Wiley book, "MDX Solutions", and I earn my living by consulting with DaisyLabs, a Business Intelligence company.
Keep Gordon's book on SQL, and my book on MDX, on your desk, and no data analysis project will scare you anymore!
Analyzing Receiver Operating Characteristic Curves Wit...
Product Description
As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are extensively used in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In this example-driven book, author Mithat Gönen illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros. Both parametric and nonparametric methods for analyzing ROC curves are covered in detail.
Topics addressed include:
* Appropriate methods for binary, ordinal, and continuous measures
* Computations using PROC FREQ, PROC LOGISTIC, PROC NLMIXED, and macros
* Comparing the ROC curves of several markers and adjusting them for covariates
* ROC curves with censored data
* Using the ROC curve for evaluating multivariable prediction models via bootstrap and cross-validation
* ROC curves in SAS Enterprise Miner
* And more!
Written for any statistician interested in learning more about ROC curve methodology, the book assumes readers have a basic understanding of regression procedures and moderate familiarity with Base SAS and SAS/STAT. Some familiarity with SAS/GRAPH is helpful but not essential.
Product Details
* Amazon Sales Rank: #514043 in Books
* Published on: 2007-10-10
* Original language: English
* Number of items: 1
* Binding: Paperback
* 152 pages
Editorial Reviews
Review
"Mithat Gönen has produced the best text to date regarding receiver operating characteristic (ROC) curves and their use in statistical analysis. He provides insight into how ROC curve analysis can be used to assess the accuracy of predictions and forecasts. The book is easy to read and comprehend and has a wealth of SAS programming examples from business, science, and medicine. The author covers all the essential approaches to analyzing receiver operating characteristic curves. I highly recommend this book!" --William F. McCarthy, Ph.D., Director, Clinical Trials,Clinical Statistics and SAS Programming, Maryland Medical Research Institute, Baltimore, MD
"ROC curves may seem quite mysterious at first; what does a "receiver operating characteristic curve" have to do with biological or biomedical phenomena? Dr. Gönen's lucid and well-organized book dispels the ROC mystery and enables ready adoption of this exciting methodology. The mixture of clearly articulated theory and development of topics with SAS code and review of SAS output throughout the text is very effective for the introduction of this material the examples are focused and well-designed. In sum, I heartily recommend Dr. Gönen's fine book." Robert Singer, M.S. PDL BioPharma --Robert Singer, M.S., PDL BioPharma
About the Author
Mithat Gönen is an Associate Attending Biostatistician at Memorial Sloan-Kettering Cancer Center, where he specializes in clinical trial design, medical diagnostic tests, and predictive model development. A SAS user since 1991, he is the author of numerous professional papers and a member of the American Statistical Association and the International Biometric Society. Mithat received a B.S. in Electrical Engineering from Middle East Technical University, an M.S. in Industrial Engineering from Stanford University, and an M.S. and Ph.D. in Statistics from Texas Tech University.
As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are extensively used in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In this example-driven book, author Mithat Gönen illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros. Both parametric and nonparametric methods for analyzing ROC curves are covered in detail.
Topics addressed include:
* Appropriate methods for binary, ordinal, and continuous measures
* Computations using PROC FREQ, PROC LOGISTIC, PROC NLMIXED, and macros
* Comparing the ROC curves of several markers and adjusting them for covariates
* ROC curves with censored data
* Using the ROC curve for evaluating multivariable prediction models via bootstrap and cross-validation
* ROC curves in SAS Enterprise Miner
* And more!
Written for any statistician interested in learning more about ROC curve methodology, the book assumes readers have a basic understanding of regression procedures and moderate familiarity with Base SAS and SAS/STAT. Some familiarity with SAS/GRAPH is helpful but not essential.
Product Details
* Amazon Sales Rank: #514043 in Books
* Published on: 2007-10-10
* Original language: English
* Number of items: 1
* Binding: Paperback
* 152 pages
Editorial Reviews
Review
"Mithat Gönen has produced the best text to date regarding receiver operating characteristic (ROC) curves and their use in statistical analysis. He provides insight into how ROC curve analysis can be used to assess the accuracy of predictions and forecasts. The book is easy to read and comprehend and has a wealth of SAS programming examples from business, science, and medicine. The author covers all the essential approaches to analyzing receiver operating characteristic curves. I highly recommend this book!" --William F. McCarthy, Ph.D., Director, Clinical Trials,Clinical Statistics and SAS Programming, Maryland Medical Research Institute, Baltimore, MD
"ROC curves may seem quite mysterious at first; what does a "receiver operating characteristic curve" have to do with biological or biomedical phenomena? Dr. Gönen's lucid and well-organized book dispels the ROC mystery and enables ready adoption of this exciting methodology. The mixture of clearly articulated theory and development of topics with SAS code and review of SAS output throughout the text is very effective for the introduction of this material the examples are focused and well-designed. In sum, I heartily recommend Dr. Gönen's fine book." Robert Singer, M.S. PDL BioPharma --Robert Singer, M.S., PDL BioPharma
About the Author
Mithat Gönen is an Associate Attending Biostatistician at Memorial Sloan-Kettering Cancer Center, where he specializes in clinical trial design, medical diagnostic tests, and predictive model development. A SAS user since 1991, he is the author of numerous professional papers and a member of the American Statistical Association and the International Biometric Society. Mithat received a B.S. in Electrical Engineering from Middle East Technical University, an M.S. in Industrial Engineering from Stanford University, and an M.S. and Ph.D. in Statistics from Texas Tech University.
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