Enterprise Web 2.0 Fundamentals Review

Average Reviews:

(More customer reviews)It's perhaps slightly surprising to see this put out by Cisco Press. They usually deal with topics closely if not explicitly tied to Cisco hardware, or to Cisco sponsored credentialling.
The book has more general scope, for the most part. It talks in broad, largely nontechnical prose, about the Web 2.0. Explaining what this means in terms of blogs, social networking, wikis and other user-generated activities. But it also has meaning in terms of the mobile user, who might access the web from a cellphone, PDA or wireless netbook.
As to how the Web 2.0 is accomplished in a technical manner, the book describes various programming languages that are popular in building such websites. Think Ajax and Ruby on Rails, for instance.
The conceptual boundary of the Web is the so-called Semantic Web, a term proposed by Tim Berners-Lee. We get some airing here about the Semantic Web. You get to appreciate that this is still early times for it. The book also brings up cloud computing. Alas, the latter term is so vague, but to the extent that it has useful meaning, the book tries to educate you on this.
The last 2 chapters are where Cisco is actively promoted. Describing how Cisco uses things like blogs in their sales group. I'm not sure quite what to make of these chapters. Is it mainly to build mindshare about how Cisco uses these ideas? For instance, it mentions how Cisco won several awards for their projects. Good for them.
The appendices are extensive and quite good, if you want to use the book as a guide to far more detailed resources on the Web. In a way, the appendices somewhat impart the book the flavour of a review article in a scholarly journal, by their copious references to original texts.

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An introduction to next-generation web technologiesThis is a comprehensive, candid introduction to Web 2.0 for every executive, strategist, technical professional, and marketer who needs to understand its implications. The authors illuminate the technologies that make Web 2.0 concepts accessible and systematically identify the business and technical best practices needed to make the most of it. You'll gain a clear understanding of what's really new about Web 2.0 and what isn't. Most important, you'll learn how Web 2.0 can help you enhance collaboration, decision-making, productivity, innovation, and your key enterprise initiatives.The authors cut through the hype that surrounds Web 2.0 and help you identify the specific innovations most likely to deliver value in your organization. Along the way, they help you assess, plan for, and profit from user-generated content, Rich Internet Applications (RIA), social networking, semantic web, content aggregation, cloud computing, the Mobile Web, and much more. This is the only book on Web 2.0 that:Covers Web 2.0 from the perspective of every participant and stakeholder, from consumers to product managers to technical professionalsProvides a view of both the underlying technologies and the potential applications to bring you up to speed and spark creative ideas about how to apply Web 2.0Introduces Web 2.0 business applications that work, as demonstrated by actual Cisco® case studiesOffers detailed, expert insights into the technical infrastructure and development practices raised by Web 2.0Previews tomorrow's emerging innovations–including "Web 3.0," the Semantic WebProvides up-to-date references, links, and pointers for exploring Web 2.0 first-handKrishna Sankar, Distinguished Engineer in the Software Group at Cisco, currently focuses on highly scalable Web architectures and frameworks, social and knowledge graphs, collaborative social networks, and intelligent inferences.Susan A. Bouchard is a senior manager with US-Canada Sales Planning and Operations at Cisco. She focuses on Web 2.0 technology as part of the US-Canada collaboration initiative.Understand Web 2.0's foundational concepts and component technologiesDiscover today's best business and technical practices for profiting from Web 2.0 and Rich Internet Applications (RIA)Leverage cloud computing, social networking, and user-generated contentUnderstand the infrastructure scalability and development practices that must be address-ed for Web 2.0 to workGain insight into how Web 2.0 technologies are deployed inside Cisco and their business value to employees, partners, and customersThis book is part of the Cisco Press® Fundamentals Series. Books in this series introduce networking professionals to new networking technologies, covering network topologies, example deployment concepts, protocols, and management techniques.Category: General NetworkingCovers: Web 2.0$40.00 USA / $48.00 CAN

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Collective Intelligence in Action Review

Average Reviews:

(More customer reviews)I was recently asked by the publisher to review Collective Intelligence in Action. The author is Satnam Alag, a Bay area engineer with a Ph.D. from the University of California, Berkeley. Dr. Alag is VP of NextBio, a specialized search engine.
The first chapter is free and so is the source code used in the book.
The book is for Java developers who want to implement "Collective Intelligence" applications in Java. It tells us about extracting and applying data from blogs, wikis and social network applications. I am not one to praise, but this book succeeds brilliantly. If you are a Java engineer and work with Web technologies, you must get this book. It covers topics such as computing similarity measures using vector models, Nai've Bayes Classifiers, inverse document frequency (idf), Machine Learning (using the Weka API), building a crawler with regular expressions, collaborative filtering (with links to open source tools), and so on.
Even if you do not work with Java, if you care for high-end Web applications, this book is for you. It reminds me of Lyon's Java¿ Digital Signal Processing book. It offers the gist of what academia knows, but focuses on what people (engineers and researchers) do in practise.
The book is not meant for academia however. There are references, but no theorem.
Disclaimer. I did not get paid to review this book, and I do not stand to gain anything if you buy the book. I have no relationship with the publisher or the author.
Further reading. A competing book is Programming Collective Intelligence: Building Smart Web 2.0 Applications by Toby Segaran. It uses Python instead of Java.

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There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob.

In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users.

Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches.

This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit.

Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard.

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Think Stats Review

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(More customer reviews)If your grasp of Programming exceeds your understanding of Basic Statistics, this book IS for you. As a University Statistics professor, I am constantly looking for reading materials that I can use to integrate Practical Statistics with programming. I am generally faced with the problem of having to mine Programming texts for Stats lessons, all too often I am faced with books that attempt to teach a programming language with examples from Freshman Statistics as an afterthought. (Too much of one, not enough of the other)
This book comes at the problem from the other side. Given that you already have a healthy grasp on programming and are trying to learn Statistics, each topic is presented with helpful, real-world data examples, and a step-by-step explanation of how to code the solutions. That makes this book excellent supplementary material for a Statistics class, or at the very least, a wonderful refresher for those returning to Statistics, with programming in mind.
Caution:
This book is NOT for you if you do NOT have a basic understanding of Programming. This book will NOT teach you to program using statistics. It is meant to teach you statistics using programming.

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If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.

Develop your understanding of probability and statistics by writing and testing code
Run experiments to test statistical behavior, such as generating samples from several distributions
Use simulations to understand concepts that are hard to grasp mathematically
Learn topics not usually covered in an introductory course, such as Bayesian estimation
Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools
Use statistical inference to answer questions about real-world data

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