Showing posts with label data mining. Show all posts
Showing posts with label data mining. Show all posts

How to Do Everything with Web 2.0 Mashups Review

How to Do Everything with Web 2.0 Mashups
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How to Do Everything with Web 2.0 Mashups ReviewThis book reminded me of Marine Corps boot camp. We did a lot of stuff, but only just enough to say we did it and not enough to learn anything from it. This book tries to cover far too many topics in a very short space. We used this book for a class I took the summer before last. It is not even really a good introduction as it leaves out many particulars needed to understand what is going on. I had to do quite a bit of internet research just to figure out much of what this book purported to teach. I say skip this book and get some more thorough books on the individual topics.How to Do Everything with Web 2.0 Mashups Overview
Want to supercharge your website with the latest searching, mapping, shopping, and imaging tools? Now you can build amazing mashups with help from this step-by-step guide. How to Do Everything with Web 2.0 Mashups shows you how to remix the best of Google, Amazon, Flickr, and eBay to create customized applications. You'll learn to use essential Web 2.0 technologies--including XML, JavaScript, XHTML, and REST--and seamlessly integrate them into your own innovative mashups.

Build dynamic mashups using XML and JavaScript

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Pro Hadoop (Expert's Voice in Open Source) Review

Pro Hadoop (Expert's Voice in Open Source)
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Pro Hadoop (Expert's Voice in Open Source) ReviewThe reason why I say this book's still a Good Buy is because Jason Venner has used Hadoop in several scenarios, and this book contains a lot of practical and time-saving tips on what mistakes to avoid or how to troubleshoot problems, making it an especially good book for Hadoop newbies. His materials on Testing and Debugging MapReduce Applications are also a value-add.
Chapter One provides detailed instructions on how to install Hadoop and how to run a test to verify that everything went fine. The author mentions that Hadoop 0.19 works best with Sun's JDK 1.6 and that although Hadoop will work on Windows with Cygwin installed, you have to be careful when specifying file paths.
Chapters Two and Three introduce basic concepts pertaining to MapReduce Jobs and Multimachine Clusters, respectively, and how "master" and "slave" nodes are configured. Chapter Four teaches you how to install, configure, and troubleshoot Hadoop Distributed File System.
Chapters Five and Six provide tutorials on the different types of inputs and outputs that a Hadoop MapReduce job can handle, and how to tune MapReduce jobs.
Chapter Seven is an excellent tutorial on how to unit test and debug MapReduce jobs, while Chapter Eight discusses more advanced MapReduce techniques for addressing more complex application requirements.
Chapter Nine walks you through the evolution of a (somewhat boring) real-world application, discussing rationales behind design changes, etc. Chapter 10 provides a few descriptive paragraphs each for various projects related to Hadoop (e.g., Pig, HBase, Mahout, ZooKeeper,etc). Finally, Appendix A is a detailed discussion of the JobConf API, JobConf being the object that controls information relating to a MapReduce job.Pro Hadoop (Expert's Voice in Open Source) OverviewIt's a very safe bet that cloud computing interest increases and in fact, a near certainty. A recent estimate from Merrill Lynch suggested a $95 billion annual market by 2013. Hadoop is at the center of cloud computing: it is one of the most searched-for, documented, and prevalent form of cloud computing data access, and even in its pre-final form is already rich enough to support a consulting business model. Anyone wishing to investigate an enterprise-level cloud computing solution will need a Hadoop book to at least investigate the possibilities.Hadoop is one of the tools that's driving today's developers to build tomorrow's Software as a Service (SaaS)-based and driven Internet applications, invested in by Yahoo, Microsoft, Google, Amazon and more. With Hadoop, developers can build tomorrow's data centers, or the next 'Microsoft Office" or 'Google Apps" - applications that are fully hosted on the Web, not the desktop - and much more.Pro Hadoop will be the first to market with a professional guide and reference to getting up to speed with using, developing and working with Hadoop, an open source Java-based cloud computing framework and platform backed by Yahoo. This book will likely time with Hadoop 1.0 release in June 2009, also around JavaOne, the world's largest Java conference at around 15,000 attendees on average.

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Collective Intelligence in Action Review

Collective Intelligence in Action
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Collective Intelligence in Action ReviewI 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.Collective Intelligence in Action Overview
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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Pro Web 2.0 Mashups: Remixing Data and Web Services (Expert's Voice in Web Development) Review

Pro Web 2.0 Mashups: Remixing Data and Web Services (Expert's Voice in Web Development)
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Pro Web 2.0 Mashups: Remixing Data and Web Services (Expert's Voice in Web Development) ReviewKudos to the author and publisher for this release.
This book is a tour de force of the subject of Mashups.
I was looking for a good book on this subject so that I could introduce it to students as part of an extra-curricular technology program in NYC and this book is perfect.
In a sentence, Mashups are created by taking data from one or more sources and making something new and useful from them.
In my opinion, the subject is very important because there is a vast amount of data that is available now. Today the challenge is not just finding data but putting to use. This book shows you how to do that.
The author's writing style is excellent, mixing theory and applications. The book is filled with hands on examples as well as references for research in each of the areas.
I believe that this book can be read by anyone interested in the subject, regardless of their technical background. For those that want to create Mashups without programming, this book shows you how. For those that want to delve into programming, everything that you need is covered including AJAX, PHP, various data formats and how to parse them, various Javascript libraries and more.
The book is laid out in four parts:
1. Remixing Information Without Programming
As the title suggests, the chapters in this section require no previous programming experience. The author walks through some specific examples, introduces terminology and analyzes how sites like Flickr and del.icio.us work so that you can get the most out of them. Tools such as Yahoo! Pipes (a browser-based visual application for Mashups and Remixing) are explored. Following along with the discussion the reader can put together a Mashup or Remix by simply understanding the concepts and using tools, but not having to delve into coding.
2. Remixing a Single Web Application Using Its API
For the person who wants to code, this part of the book jumps right in discussing the Flickr API, PHP usage, XML processing and more. From there the discussion moves to other APIs and using AJAX/Javascript widgets.
3. Making Mashups
This section starts by delving into the ProgrammableWeb website. Showing how to find what resources are available, studying existing Mashups via which APIs they use and how to go about creating new ones. From there XMLHttpRequest and Javascript libraries such as YUI are covered and a step-by-step example is given using the previously discussed techniques. Lastly, the author addresses issues around implementing Mashups on your site including standards, accessibility and your own API. I was glad to see these topics covered as sometimes in the haste of getting something online, they can be overlooked.
4. Exploring Other Mashup Topics
This final section of the book covers a large range of interesting topics such as Map-based Mashups, Social Bookmarking, Calendars, Online Storage, Desktop and Office Suites, Embeddable Data Formats and Searches.
As you can see, there's a lot of information covered in this book. In my opinion, everything that one could want on the subject and written in such a way that you want to keep reading, exploring and creating your own Mashups.
I highly recommend this book - so far, it has been my favorite read of 2008!Pro Web 2.0 Mashups: Remixing Data and Web Services (Expert's Voice in Web Development) OverviewMashups are hugely popular right now, a very important topic within the general area of Web 2.0, involving technologies such as CSS, JavaScript, Ajax, APIs, libraries, and server-side languages (such as PHP and ASP.NET.) This book aims to be the definitive tome on Mashup development, to stand in the middle of all the other, more API specific books coming out on Google Maps, Flickr, etc.The book shows you how to create real world Mashups using all the most poplar APIs, such as Google Maps, Flickr, Amazon Web Services, and delicious, and includes examples in multiple different server-side languages, such as PHP, Java, and .NET. It will have a large target audience, but still deliver an effective and engaging learning experience, regardless of the specific technologies the reader prefers to use.

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Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis Review

Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis
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Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis ReviewFrom a technical perspective you won't find details about what algorithms are used and how to implement them in the real world. I came to this book looking for some field applications of DM, Instead a found a very interesting introduction to the kind of decisions related to crime prosecution and prevention without deep technical details.Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis Overview

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Programming Collective Intelligence: Building Smart Web 2.0 Applications Review

Programming Collective Intelligence: Building Smart Web 2.0 Applications
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Programming Collective Intelligence: Building Smart Web 2.0 Applications ReviewThis book is probably best for those of you who have read the theory, but are not quite sure how to turn that theory into something useful. Or for those who simply hunger for a survey of how machine learning can be applied to the web, and need a non-mathematical introduction.
My area of strength happens to be neural networks (my MS thesis topic was in the subject), so I will focus on that. In a few pages of the book, the author describes how the most popular of all neural networks, backpropagation, can be used to map a set of search terms to a URL. One might do this, for example, to try and find the page best matching the search terms. Instead of doing what nearly all other authors will do, prove the math behind the backprop training algorithm, he instead mentions what it does, and goes on to present python code that implements the stated goal.
The upside of the approach is clear -- if you know the theory of neural networks, and are not sure how to apply it (or want to see an example of how it can be applied), then this book is great for that. His example of adaptively training a backprop net using only a subset of the nodes in the network was interesting, and I learned from it. Given all the reading I have done over the years on the subject, that was a bit of a surprise for me.
However, don't take this book as being the "end all, be all" for understanding neural networks and their applications. If you need that, you will want to augment this book with writings that cover some of the other network architectures (SOM, hopfield, etc) that are out there. The same goes for the other topics that it covers.
In the end, this book is a great introduction to what is available for those new to machine learning, and shows better than any other book how it applies to Web 2.0. Major strengths of this book are its broad coverage, and the practicality of its contents. It is a great book for those who are struggling with the theory, and/or those who need to see an example of how the theory can be applied in a concise, practical way.
To the author: I expect this book will get a second edition, as the premise behind the book is such a good one. If that happens, perhaps beef up the equations a bit in the appendix, and cite some references or a bibliography for those readers interested in some more in depth reading about the theory behind all these wonderful techniques. (The lack of a bibliography is why I gave it 4 stars out of 5, I really think that those who are new to the subject would benefit greatly from knowing what sits on your bookshelf.)Programming Collective Intelligence: Building Smart Web 2.0 Applications OverviewWant to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general--all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:
Collaborative filtering techniques that enable online retailers to recommend products or media
Methods of clustering to detect groups of similar items in a large dataset
Search engine features--crawlers, indexers, query engines, and the PageRank algorithm
Optimization algorithms that search millions of possible solutions to a problem and choose the best one
Bayesian filtering, used in spam filters for classifying documents based on word types and other features
Using decision trees not only to make predictions, but to model the way decisions are made
Predicting numerical values rather than classifications to build price models
Support vector machines to match people in online dating sites
Non-negative matrix factorization to find the independent features in adataset
Evolving intelligence for problem solving--how a computer develops its skill by improving its own code the more it plays a game
Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

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An Introduction to Search Engines and Web Navigation Review

An Introduction to Search Engines and Web Navigation
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An Introduction to Search Engines and Web Navigation ReviewThe first chapters of the book provide an extensive introduction to search engines and navigation. No formal prerequisites are required; any Web enthusiast will enjoy reading the book. These chapters comprise of background and history of the Web, navigation and searching, search engine architecture and different types of search engines. In addition to the basics, additional topics covered are navigation (aka surfing), the interplay between search and navigation, Web data mining, personalization, the mobile web, social networks, collaborative filtering and Weblogs (aka Blogs).
The book goes far beyond simple searching and navigation; it provides a comprehensive overview of the current research fronts in areas related to Web search engines and navigation.
The text is highly readable with a large number of illustrations and examples. It can serve as an excellent textbook both for an introductory and a more advanced course of Web search and navigation. Each chapter starts with a listing of objectives and ends with a set of exercises relevant to the topics covered in the chapter. Students will especially benefit from the non-technical descriptions and clear explanations of the concepts.
The book is also a great reference source for researchers and IT professionals: it includes 410 references to articles, and 202 references to Web pages and resources. I highly recommend the book.
An Introduction to Search Engines and Web Navigation OverviewThis book is a second edition, updated and expanded toexplain the technologies that help us find information on the web. Search engines and web navigation tools have become ubiquitous in our day to day use of the web as an information source, a tool for commercial transactions and a social computing tool. Moreover, through the mobile web we have access to the web's services when we are on the move. This book demystifies the tools that we use when interacting with the web, and gives the reader a detailed overview of where we are and where we are going in terms of search engine and web navigation technologies.

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Spidering Hacks Review

Spidering Hacks
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Spidering Hacks ReviewThe `Hacks' series from O'Reilly seems to be breeding as fast as virii in a Windows network - every time you turn around another one. While the writing and editing have remained high some such as `eBay Hacks' have not really had great material. `Spidering Hacks' is an improvement almost back to the quality I remember in the last contribution from Calishain, `Google Hacks'.
She and Kevin Hemenway have taken a fairly complex topic, spidering and scraping web sites and reduced it to manageable chunks in their hundred hacks. The writing has the same light, readable feel you can quickly grow to expect from O'Reilly. Certainly I have never found myself faulting their editing.
There are some caveats. It seems that O'Reilly and Dornfest (the Editor of this book and the series) have fallen in love with having a hundred hacks and little in the way of an introduction. I think this may have been a better book if it was done as 90 `hacks' and had a much larger introduction as the first chapters hacks are all too light and more truly introductory material such as how a HTML page is built and how to properly register your spider. Given that only someone with a fair amount of web knowledge is going to consider spidering a website in the first place then this early material is way too slight. From Hack 9 on it quickly gets down to useful and informative chunks in each and no longer feels `lightweight'.
This may be a reflection on trying to extend the `Hacks' series into places it has to be forced. While the format worked well for Google and Amazon I felt the entire topic of eBay too light for a topic in this series and perhaps spidering is too heavy or complex. If this book had been written in a more traditional format some of my complaints would disappear.
All the examples are in Perl and the serious part of the book starts with examples using LWP::Simple to grab a page before going on to LWP::UserAgent and much more complex requests using authentication, custom headers and posting form data. It also covers using curl and wget.
Then it gets down to the nitty gritty of scraping using HTML:Treebuilder and HTML:TokeParser. This is all further expanded through the next few hacks until starting at Hack 39 through to 89 there are a good series of examples (perhaps a few too many). Finally there are two chapters on maintaining your collection and `Giving Back To The World' which tells how to make it easy to scrape your site and using RSS.
O'Reilly have a page for the book with ten example hacks, index, Table of Contents and errata and you can also visit hacks.oreilly.com for the same ten hacks with the possibility of more being added.
As a whole this volume seems a little thin. If you've been doing the maths then you've realised that only about thirty of the hundred hacks actually give any details on building and running a serious web spider. Sure, a number of the examples provide good information on how to perform various tasks and some of the last eleven hacks are good to know but in all the book feels like it lacks solid information throughout. A bit more information on various crawling and page parsing techniques would have been good.
After that criticism I'm now surprising myself, I'm going to recommend this book. This isn't a large field and when you consider that most other books on writing spiders and crawlers are less than practical and more than expensive "Spidering Hacks" has many good points. It's written for the practical Perl programmer, it examines several methods and gives lots of examples and while not cheap it's certainly inexpensive. Given that I found it both useful and inspiring the complaints above may be a little like nitpicking. I should also say that I found this volume immensely useful in writing my own spider and scraper (it gets a list of new books from the web sites of several publishers.) I have to be honest and admit that there are three publishers, O'Reilly, Addison Wesley and Prentice Hall, from whom I expect a decent standard and criticise a little harder when they move from that norm. If this book had come from SAMS or Wrox I may well have not looked quite so hard for flaws and been a little more generous in my treatment of the ones I found.
That said, I recommend this book to you if you want a practical introduction to building a web spider in Perl.Spidering Hacks Overview
The Internet, with its profusion of information, has made us hungry for ever more, ever better data. Out of necessity, many of us have become pretty adept with search engine queries, but there are times when even the most powerful search engines aren't enough. If you've ever wanted your data in a different form than it's presented, or wanted to collect data from several sites and see it side-by-side without the constraints of a browser, then Spidering Hacks is for you.

Spidering Hacks takes you to the next level in Internet data retrieval--beyond search engines--by showing you how to create spiders and bots to retrieve information from your favorite sites and data sources. You'll no longer feel constrained by the way host sites think you want to see their data presented--you'll learn how to scrape and repurpose raw data so you can view in a way that's meaningful to you.

Written for developers, researchers, technical assistants, librarians, and power users, Spidering Hacks provides expert tips on spidering and scraping methodologies. You'll begin with a crash course in spidering concepts, tools (Perl, LWP, out-of-the-box utilities), and ethics (how to know when you've gone too far: what's acceptable and unacceptable). Next, you'll collect media files and data from databases. Then you'll learn how to interpret and understand the data, repurpose it for use in other applications, and even build authorized interfaces to integrate the data into your own content.By the time you finish Spidering Hacks, you'll be able to:

Aggregate and associate data from disparate locations, then store and manipulate the data as you like
Gain a competitive edge in business by knowing when competitors' products are on sale, and comparing sales ranks and product placement on e-commerce sites
Integrate third-party data into your own applications or web sites
Make your own site easier to scrape and more usable to others
Keep up-to-date with your favorite comics strips, news stories, stock tips, and more without visiting the site every day
Like the other books in O'Reilly's popular Hacks series, Spidering Hacks brings you 100 industrial-strength tips and tools from the experts to help you master this technology.If you're interested in data retrieval of any type, this book provides a wealth of data for finding a wealth of data.

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Beautiful Data: The Stories Behind Elegant Data Solutions Review

Beautiful Data: The Stories Behind Elegant Data Solutions
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Beautiful Data: The Stories Behind Elegant Data Solutions Review"Beautiful Data" is a collection of essays on data; how people have transformed it, worked within its confines, and offers a glimpse of where we might go. Many of the essays are wonderful snippets into how some people perceive data while others fall flat. Overall its a mostly enjoyable read that helps open up your mind to new potentials.
First a disclaimer; I am not a data person. However I've been involved, fairly heavily, in the data field. In the parlance of the world, I'm a back end person. However I'm always trying to think about the front end; how will things be used and what information can we gleen from the system (or systems). With that in mind, this is a book that speaks to me - its all about the front end.
Some of the best essays in the book would be:
The first essay by Nathan Yau he talks very much about user created data and personal databases (knowledge bases). What's exciting here is how he takes data already out there, data you have provided, and creates something useful and yes, beautiful, out of it.
The Second essay by Follett and Holm really gets down to how if you want the data, you need to present it in a way that brings people into the process. As someone who has a slight crush on the statistics and practices in polling (and designing poll questions) this essay really was a fascinating read.
The third essay by Hughes detailed how he handled images on the Mars mission. There wasn't anything here that wasn't done in embedded systems 15 years ago; still it was a great walk down memory lane since I used to program embedded imaging systems.
Chapter 4 really hit home PNUTShell is cloud storage and data processing in real time. This really is the stuff of the future.
Chapter 5 by Jeff Hammerbacher really didn't offer too many insights but his writing style is fluid and fun plus he offered a glimpse into how Facebook grew.
We then have the slow section of the book - Chapter 8 on distributed social data had promise but it read more like a company white page than an interesting article. Same with Chapter 12 [...].
Thankfully chapter 10 on Radiohead's "House of Cards" video was there - and here we are presented with true beauty in data - beautiful enough to create a music video out of!
I'm still on the fence with Chapter 13 - What Data Doesn't Do. It was an interesting chapter but it felt both too long and too short at the same time. I almost felt that in the author, Coco Krumme, were to write a book on this topic, I'd want to read it. However her essay was not the right vehicle.
Finally, the last chapter - "Connecting Data" was a truly inspiring piece; one that offers up paths for the future. I am sure a few start ups will form over the questions posed in by Segaran (or maybe the questions to the questions).
Overall there were enough strengths to overcome the weak chapters. My main complaints are trivial; poor binding of the book, too many PhD candidate papers and not enough from out in the trenches. I'd love to see something from Stonebreaker here; its hard to talk about beautiful data and not have him in it. Or forget [...]and talk about many eyes. Or map reduce. Still, "Beautiful Data" succeeds. It opened up my mind to different possibilities for data representation and usage.
Beautiful Data: The Stories Behind Elegant Data Solutions Overview
In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video. With Beautiful Data, you will:

Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web
Learn how to visualize trends in urban crime, using maps and data mashups
Discover the challenges of designing a data processing system that works within the constraints of space travel
Learn how crowdsourcing and transparency have combined to advance the state of drug research
Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data
Learn about the massive infrastructure required to create, capture, and process DNA data

That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include:
Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran

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Advanced Web Metrics with Google Analytics Review

Advanced Web Metrics with Google Analytics
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Advanced Web Metrics with Google Analytics ReviewBrian Clifton's Advanced Web Metrics with Google Analytics should, for all intents and purposes, have the term "Advanced" in bold, possibly in a gigantic type font with fun colours and exclamation marks.
The first 3-5 chapters start innocently enough, and if you have been involved in web analytics or read any other material on the topic you will find it largely rehashes what you already know with a few nuggets of gold throughout. For instance, Brian's discussion as it pertains to Google's tracking of data and its privacy implications offers a wonderful metaphor relating to personal identifiable information, though his emphasis curiously seems to be trying to convince the reader, rather than positioning it as a tool that one can use to assuage stakeholders or individuals who are not sold on analytics.
Chapter 4, which aforementioned is innocent enough, gives one a glimpse of what is to come when Brian delves into a discussion on regular expressions (in order to filter data via GA's inline filter). If you are unfamiliar with a command line interface, advanced search expressions or anything of the sort, good luck. Even if you are, this section comes WAY out of left field and perhaps could have been saved for later, but the information itself is useful and I've been utilizing a number of the expressions ever since.
Chapter 7 is where this book really begins, and Brian starts it off by giving an in depth explanation of how Google tracks pages and summarily applies that logic to show how one can track things like dynamic URL's (rewriting them along the way), tracking file downloads, partially completed forms (cool stuff), and E-Commerce settings (with some neat tricks and workarounds for frequent issues and problems), Flash, and a whole host of things. All of this is done very clearly, but if you don't have some technical aptitude/background, you're going to struggle.
After the largely technical Chapter 7, Brian shifts back into a less technically focused discussion on best practices, including a fantastic write up on goals and funnels (including excellent examples for both). His knowledge and ability to write in a clear form is particularly visible when he discusses segmentation, which, while other authors have done a good job championing, Brian, at least to me, easily blows them out of the water. If you're not technically inclined, this is a great section, though you may still be a bit perturbed by the depth of the filter settings.
Chapter 9 is worth the purchase of this book alone, IF you can follow it. For reference, it's prefaced with the words "In this chapter I assume you have a strong understanding of JavaScript" and it holds true. In this chapter you learn a whole whack of cool things, and I literally have a pile of notes sitting on my desk as a result. Brian goes into everything from adding custom search engines to your GA results, tracking error pages and broken links and tracking referral url's from pay-per-click networks to differentiating links to the same page via site overlay. There's just tons of great tricks and tips in this section, and it's clear to anyone with a clue that not only does the author of this section have an understanding of Google that vastly exceeds your own, but that he can write about it in a clear, easy to understand (given the nature of the topic) way.
Chapter's 10 and 11 are also excellent, and one does not need to be overly technical to understand them. The former discusses KPI's in an extremely clear, helpful manner and even discusses creating reports based on specific job roles. In the process, Brian reveals a bunch of custom KPI's that he has created that are fantastic--which is to say, if you are reading this section do not skip a job role just because it's not applicable, there's lots of gold to be mined.
Chapter 11 focuses on real world tasks, such as diagnosing problem pages, delves deeper into funnels and how to use Google optimizer and is a great read that, no matter who you are, I promise you will learn something from.
In summary, if you are technically inclined and can follow some of the more esoteric topics, this book is an absolute must have--buy it right now. If you are not so technically inclined, there is still lots of value in chapters, 8, 10 and 11 which in my opinion still would merit a purchase, but of course, you are not getting the same value. So, as I said to begin this admittedly long review, this book is phenomenal, but there is one big caveat. You need to have some technical knowledge to truly appreciate how much valuable information it provides.
Advanced Web Metrics with Google Analytics OverviewAre you getting the most out of your website? Google insider and web metrics expert Brian Clifton reveals the information you need to get a true picture of your site's impact and stay competitive using Google Analytics (GA) and the latest web metrics methodologies.Which marketing campaigns work best? How do you quantify their success? What indicators should you track? Packed with techniques and insider secrets not documented elsewhere, this book has the expert guidance you need to enhance your brand and increase your site's ROI.

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Internet Searches for Vetting, Investigations, and Open-Source Intelligence Review

Internet Searches for Vetting, Investigations, and Open-Source Intelligence
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Internet Searches for Vetting, Investigations, and Open-Source Intelligence ReviewI have been a private investigator for more than 25 years. When I started in this business computers were scarce and the Internet had not yet been commercialized. Everything was done with a pencil and telephone. I have a lot of experience so it is hard for me to find books that are useful. I buy books hoping to learn one or two new things. Edward J. Appel, a retired FBI agent is the author. His company has done work for me so I knew the quality of his work and assumed his book would be at the same level as his investigative efforts. I wasn't disappointed.
The book is 320 pages and broken into 4 sections. Appel begins with a chapter about behavior and technology which orients the investigator/analyst on the growth and use of the Internet. He discusses the usefulness of the Internet as an investigative tool and the transformations the Internet is making through social and technological advances. Along with the benefits for investigators comes the darker side of the web, and Appel examines its criminal exploitation.
The first section provides a great introduction and is geared toward corporate investigators and security personnel tasked with monitoring IT systems, vetting employees and guarding company intellectual property. In Section 2 Appel outlines legal and policy issues related to using information from the Internet in investigations. He identifies liability and privacy issues and laws addressing these concerns such as the Fair Credit Reporting Act. He also dedicates a chapter to litigation, defamation, and invasion of privacy torts.
Appel develops a framework for preparation and planning of successful Internet research. He covers basic information about search engines, metasearch engines, social networking sites and search terms.
I found the chapters Automation of Searching and Internet Intelligence Reporting to be the most enlightening. Reducing time spent searching and analyzing information, seems like a no-brainer. But I would bet the number of investigators who have looked for automated solutions to their collection efforts is small. The Internet Intelligence Reporting section recommends the format and organization of a report as well as what to include and how to cite sources.
Internet Searches for Vetting, Investigations, and Open-Source Intelligence, like many trade publications, is on the pricey side. However it delivers with content and is an easy read. It met my criteria for a successful investigations book because I learned much more than two new things.
Internet Searches for Vetting, Investigations, and Open-Source Intelligence OverviewIn the information age, it is critical that we understand the implications and exposure of the activities and data documented on the Internet. Improved efficiencies and the added capabilities of instant communication, high-speed connectivity to browsers, search engines, websites, databases, indexing, searching and analytical applications have made information technology (IT) and the Internet a vital issued for public and private enterprises. The downside is that this increased level of complexity and vulnerability presents a daunting challenge for enterprise and personal security.Internet Searches for Vetting, Investigations, and Open-Source Intelligence provides an understanding of the implications of the activities and data documented by individuals on the Internet. It delineates a much-needed framework for the responsible collection and use of the Internet for intelligence, investigation, vetting, and open-source information. This book makes a compelling case for action as well as reviews relevant laws, regulations, and rulings as they pertain to Internet crimes, misbehaviors, and individuals' privacy. Exploring technologies such as social media and aggregate information services, the author outlines the techniques and skills that can be used to leverage the capabilities of networked systems on the Internet and find critically important data to complete an up-to-date picture of people, employees, entities, and their activities. Outlining appropriate adoption of legal, policy, and procedural principles-and emphasizing the careful and appropriate use of Internet searching within the law-the book includes coverage of cases, privacy issues, and solutions for common problems encountered in Internet searching practice and information usage, from internal and external threats. The book is a valuable resource on how to utilize open-source, online sources to gather important information and screen and vet employees, prospective employees, corporate partners, and vendors.

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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) Review

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) ReviewI'm surprisingly please with this book. I've been reading up on the topic and associated algorithms in other books for some time; I'm a software developer but don't have a statistics background, and so felt a lot of the texts were too focused on the math and the theory while being thin on content when it came to "rubber hitting the road", or even using clear, simple examples and straight-forward notation.
This book is so well-written that it communicates the concepts clearly, lucidly and in an organized fashion. The section that introduces Bayesian probability was drop-dead simple to follow. Quite frankly, having read a few other treatments on it, I can now say that everything else I read before this was overly complicated. Brevity is the soul of wit, no?
To the reviewer who criticized the authors use of words to describe equations: This is what the authors intended to do. Would you fault them for writing in English if you wanted Greek? Not everyone who can benefit from applied data mining has the requisite background to understand the nitty gritty mathematics, nor should they have to, if they just want to understand the behavior and practical applications of the technology.Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) Overview

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Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites Review

Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites
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Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites ReviewMining the Social Web does a great job of introducing a wide variety of techniques and wealth of resources for exploring freely available social data and personal information. If you are willing to spend the time tinkering with the examples, the book is pure fun. It offers a nice compliment to Segaran's Programming Collective Intelligence: Building Smart Web 2.0 Applications. The two books overlap but where they do offer different perspectives and explanations of common techniques (e.g., TF-IDF, cosine similarity, Jaccard index). If you are well-versed in data mining the web you may find much of the discussion familiar. If you have only been casually engaged to date, your toolbox will fill quickly.
In order to work with the book's examples related to LinkedIn and Facebook you really need to have a robust collection of connections. In terms of the source code itself, most of it worked as is. I wasn't able to install the Buzz library which limited my interaction with material in chapter 7 and opted to not get involved with the LinkedIn or Facebook but found the discussions around them easy to follow. By far my favorite chapter in the book was chapter 8, "Blogs et al.: Natural Language Processing (and Beyond)..." It was quite fascinating and caused my reading list to grow considerably.Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites Overview
Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they're talking about, or where they're located? This concise and practical book shows you how to answer these questions and more. You'll learn how to combine social web data, analysis techniques, and visualization to help you find what you've been looking for in the social haystack, as well as useful information you didn't know existed.

Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.

Get a straightforward synopsis of the social web landscape
Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, and LinkedIn
Learn how to employ easy-to-use Python tools to slice and dice the data you collect
Explore social connections in microformats with the XHTML Friends Network
Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection
Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits

"Let Matthew Russell serve as your guide to working with social data sets old (email, blogs) and new (Twitter, LinkedIn, Facebook). Mining the Social Web is a natural successor to Programming Collective Intelligence: a practical, hands-on approach to hacking on data from the social Web with Python." --Jeff Hammerbacher, Chief Scientist, Cloudera

"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google


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Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart Review

Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart
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Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart ReviewIs it a new brand of cereal? Or maybe it's a granola bar, or a chunky peanut butter spread? Then again, could it be the latest infomercial exercise device designed to give you the six pack abs you've always dreamed of but know in your heart of hearts you'll never achieve? Actually, it's a book - the title a product of the very methods the book describes. Here's what SUPER CRUNCHERS says.
(1) Mathematical regression models generated from large datasets often generate better predictions than human experts, and they provide supporting information on the predictive weight and reliability of each explanatory variable.
(2) Well-crafted experiments using randomized trials and control groups provide good market research and behavioral analysis results.
(3) Technological advances - the Internet, massive data storage devices, rapid computation, broadband telecommunication - are making it possible to share more sources of information and create ever-larger databases for analysis.
(4) Today's companies engage in multiple forms of market research by creating and using large databases and large-scale randomized trials.
(5) Many phenomena conform to normal distributions in which 95% of the population will be found within two standard deviations of the mean, the5% balance generally divided evenly in the two tails.
That's it. I just saved you $25.00 U.S. and a half-dozen or more hours learning how a guy from Yale named Ian Ayres collected a bit of information about applied mathematical techniques that have been in practical use for decades, packaged them up, palmed them off as something new, and cooked up the ridiculous name Super Crunching to describe an ostensibly new technological development. Yet "Super Crunching" is nothing more than the author's marketing hype for a couple of standard mathematical methodologies, a creation of nothing from something. There's no new breakthrough here, no new paradigm.
Yes, the anecdotal information about the future prices of wine vintages, Capital One's teaser offerings, and evidence-based medical diagnosis are interesting (hence the two stars rating). The rest, however, is neither prescriptive nor sufficiently critically analytical. Should we go out shopping for a Super Cruncher tomorrow? Should we delight in the increased accuracy of data-driven modeling and prediction, or should we fear the implied manipulation of our desires and the incessant, single-minded drive toward maximum profit at the expense of creativity? Do we really want movies and books to be developed from mathematical models like Epagogix? Do we really want our every keystroke on the Internet to be fodder for market research that manipulates us in response? John Kenneth Galbraith, among others, warned of exogenous, manufactured demand decades ago.
SUPER CRUNCHERS is part business tome, part econometric paean, and part sociology book, but not fully any of the three. No matter how many time the author uses words like "cool" and "humongous" and "amazing," it's still regrettably a "No Sale" even for someone like me who enjoys reading about applied mathematics.
Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart Overview

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