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Featured Blog Posts – March 2013 Archive (22)

Invented by a data scientist: the first anti-scam

By anti-scam, I mean a scam where the victim makes more money by participating in the scam.

This scam works as follows:

  • You send money to the data scientist - AKA the scammer - and he purchases lottery tickets with…
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Added by Mirko Krivanek on March 28, 2013 at 9:30pm — 8 Comments

Big Analytics - San Francisco, May 1st

Data from customer interactions is growing at exponential rates. While many companies are storing more information about their business, customers, influencers, and competitors than ever before, some key questions and challenges need to be answered before it can impact…

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Added by Vincent Granville on March 28, 2013 at 11:30am — 1 Comment

Here's what your home will be worth, in 12 months

Or the home you would like to buy. Using Zillow forecasts, I obtained the following predictions, clearly indicating strong recovery for the West Coast, according to Zillow.

You can easily retrieve this data by entering a city on Zillow's location box, then clicking on any…

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Added by Vincent Granville on March 26, 2013 at 11:00pm — 1 Comment

Weekly Digest - March 25

Featured on DSC, Big Data News and AnalyticBridge
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Added by Vincent Granville on March 24, 2013 at 10:24pm — No Comments

A few more visualization resources

This one is a Javascript library to produce images for web documents. Here's some sample output:…

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Added by Vincent Granville on March 24, 2013 at 1:00pm — No Comments

WSJ: HP Piloted Program to Predict Which Workers Would Quit

Joel Schectman at the Wall Street Journal wrote about a story broken in my new book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

 

Wall Street Journal Article:

Book: HP Piloted Program to Predict Which Workers Would Quit

 

Joel Schectman, Wall Street Journal

 

Hewlett Packard Co. tested a predictive scoring system that attempted…

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Added by Eric Siegel on March 20, 2013 at 2:19pm — No Comments

Business Intelligence ROI Remains Elusive; A next-generation approach to “ease of use” may hold the answer

On March 6th, 2013 the Fitzgerald Analytics team attended the quarterly symposium of the TDWI NYC Tri-State Chapter.  …

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Added by Jaime Fitzgerald on March 20, 2013 at 11:30am — No Comments

Two more interesting graphs

The first one is about NCAA. Check out the original and fully interactive version (you can click on nodes to get details) with description, at http://thepowerrank.com/visual/NCAA_Tournament_Predictions.

The second one is from me,…

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Added by Vincent Granville on March 18, 2013 at 8:00pm — 1 Comment

Another cute graph

Not sure how this firework graph was produced. It "shows" 10 million emails sent through the Yahoo! Mail service in 2012, a team of researchers used the R language to create a map of countries whose citizens email each other most frequently. Click here for another…

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Added by Vincent Granville on March 14, 2013 at 11:30am — No Comments

Model Risk: When is a business analytics model ‘validated’?

In Jorge Luis Borges’ parable “On Rigor in Science” (“Del rigor en la ciencia”), a lost empire attains such perfection in the art of cartography that a one-for-one scale map of the empire is produced, laid-out across the land.  In time, the creation is understandably deemed useless and subsequent generations ambivalently witness the decay of the map (Borges, 1975).  Borges’ critique is that of a science which seeks to perfectly validate, one-to-one, its…

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Added by Scott Mongeau on March 14, 2013 at 2:48am — No Comments

14 questions about data visualization tools

Questions to ask when considering visualization tools:

  1. How do you define and measure the quality of a chart?
  2. Which tools allow you to produce interactive graphs or maps?…
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Added by Vincent Granville on March 13, 2013 at 1:30pm — 4 Comments

Stock trading strategies - my first articles

Some of my old articles published in 2001, but still worth reading. Lots of good data science advice in it.

Pitfalls in Optimizing Statistical Trading Strategies. Part I: Over-Parametrization.…

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Added by Vincent Granville on March 13, 2013 at 1:00pm — 1 Comment

Get "Predictive Analytics" - the Book - and Enjoy Free Online Training

Predictive Analytics: GET THE BOOK AND RECEIVE FREE ONLINE TRAINING

April 3rd is "Predictive Analytics" Day - not the science, the book! To build awareness of Eric Siegel's new, acclaimed book, "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" (published by Wiley Feb. 19), we're providing an offer ya can't refuse.

ORDER THE BOOK ON APRIL 3 VIA AMAZON (under $15) FOR:

1. Free access to the first of four modules of the…

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Added by Eric Siegel on March 12, 2013 at 11:04am — No Comments

Weekly Digest - Mar 11

From the Editor

If you haven't done so yet, we invite you to join Data Science Central, its channels …

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Added by Vincent Granville on March 10, 2013 at 8:39pm — No Comments

Unstructured Data Really Isn't

Unstructured Data Really Isn’t

Bradley S. Fordham, PhD (www.linkedin.com/in/drbradleyfordham)

The (ART+DATA) Institute

The term “unstructured data”, is truly an oxymoron.  All data has structure, and in fact most…

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Added by Zach Piester on March 10, 2013 at 5:20pm — 1 Comment

Why bother building a model while you have a good human doing the work?

Stunned by the Senior Management's basic and fundamental question, I spent a lot of hard time thinking through it. Finally I get part of the ultimate answer: Predictive Analytics move faster and more frequent than human being. What I mean is:

Predictive model is run to react to every change of independent variables: Building a good model of relating consumer's purchase behavior is only part of the story. What is more important is the trigger of the model can be defined and run at a…

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Added by Jeffrey Ng on March 9, 2013 at 8:55am — 7 Comments

Unleashing intelligence through natural language (Part 1 - Autonomously generated questions about gaps in the knowledge)

This is the first of a series of blogs in which I will reveal and explain rules of intelligence contained within grammar, that can be utilized to unleash intelligence in software. These rules are extremely simple, but still undiscovered by scientists.



Current state:

Systems generating questions already exists. However, their questions are useless, because the original sentence - from which the question is derived - already holds to the answer.



A…

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Added by Menno Mafait on March 9, 2013 at 1:30am — No Comments

2013 Data Miner Survey

Data collection for the 2013 Data Miner Survey will be extended until 4/22/13.  

Several people have asked for this extension, so the survey can be announced in newsletters and at conferences.
Thank you for…
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Added by Vincent Granville on March 8, 2013 at 11:07am — No Comments

Open for comments: Data Science Code of Professional Conduct

We are seeking comments and suggestions on a proposed "Data Science Code of Professional Conduct".

Data science is an independent profession. Data scientists have a higher calling than just technical skills. We have a duty to use data science to make life, business and government better.

Six (6) key reasons why data science needs a voluntary code of conduct:

1. to establish data science as a true science and profession distinguished from data analysts, statisticians,…

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Added by Michael Malak on March 7, 2013 at 9:39am — 1 Comment

Introduction to QuantLib Development with Luigi Ballabio

"Luigi is a great instructor, very helpful and the most authoritative voice on the subject"

"The exercises were very good!"

"Thank you Luigi, it was a great course!"

"Contact with the instructor was excellent!"

April 24 - 28th, 2013, London, UK

The goal of this three-day intensive hands-on course is to take a bird-eye look at the design of the QuantLib library as well as its rationale, to examine its implementation, and thus to…

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Added by Jacob Bettany on March 5, 2013 at 12:30pm — No Comments

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