R and SAS- Together again at PAWS

Two of my favorite speakers ( though maybe not favorite to each other) speak at PAWS ,

Anne Milley from SAS and David Smith, REvolution Computing.Also a great author and writer, Stephen Baker from Numerati ( that mathematical equivalent of The Godfather). More events at the link below.

Hmmmm- I hope they attend each other’s sessions just to keep up, but is that asking too much?


useR Meeting
Room: Magnolia
– Sponsored by  Please join the group at www.meetup.com/R-users-DC/

R is an open source programming language for statistical computing, data analysis, and graphical visualization. R has an estimated one million users worldwide, and its user base is growing. While most commonly used within academia, in fields such as computational biology and applied statistics, it is gaining currency in commercial areas such as quantitative finance and business intelligence.

Among R’s strengths as a language are its powerful built-in tools for inferential statistics, its compact modeling syntax, its data visualization capabilities, and its ease of connectivity with persistent data stores (from databases to flatfiles).

In addition, R is open source nature and extensible via add-on “packages” allowing it to keep up with the leading edge in academic research.

For all its strengths, though, R has an admittedly steep learning curve; the first steps towards learning and using R can be challenging.

This DC R Users Group is dedicated to bringing together area practitioners of R to exchange knowledge, inspire new users, and spur the adoption of R for innovative research and commercial applications.

Wednesday October 21, 2009

Registration & Continental Breakfast

Room: Magnolia
Opportunities and Pitfalls:
What the World Does and Doesn’t Want from Predictive Analytics

Mathematicians and statisticians are churning through mountains of data in their efforts to model and predict human behavior. The goal is to optimize every function possible, from sales and marketing to the enterprise itself. These Numerati are guided by the two dominant models of the late 20th century, the modeling of financial markets and of industrial systems. How do humans fit into these systems? And what will their response be when the analytic systems appear to misunderstand them or invade their privacy?

Stephen Baker joins PAW to directly address the Numerati. In his keynote presentation, Mr. Baker will guide us toward the untapped goldmines where predictive analytics will be embraced and thrive, and teach us to anticipate and maneuver around two central pitfalls: Consumer misperception of us, and our inadvertent mistreatment of them.

Moderator: Eric Siegel, Program Chair, Predictive Analytics World

Speaker: Stephen Baker, BusinessWeek – author, The Numerati

Platinum Sponsor Presentation
Room: Magnolia
Strength in Numbers: ACE!

As more organizations are beginning their analytical journey or reinvigorating their existing efforts, Analytic Centers of Excellence (ACEs) are helping them along the way. The interest in ACEs is growing across industries as organizations seek better ways to tap into their analytic infrastructure-most importantly, scarce high-end analytic expertise to improve results. We will highlight valuable best practices for achieving greater analytic bandwidth realizing more and better evidence-based decisions.

Moderator: Eric Siegel, Program Chair, Predictive Analytics World

Speaker: Anne Milley, Senior Director of Tech. Product Marketing, SAS

Losing a Million Bucks: Netflix Prize Interview

I ( and collective pseudo geeks) across the world lost a potential million dollars when the following team won the Netflix prize. In disgust, I just renewed my Netflix subscription and noticed a 10% increase in the way I liked them.

Jokes apart, here is an except ( perhaps one of the few ever) of an interview of the Netflix winners done by the great Eric Siegel, Phd.

Eric is conference chair of the Predictive Analytics Conference ( a King Arthur’s round table conference on all the shining knights of the data analytic’s world)


[ES] With no relevant background in statistics — let alone product recommendations specifically — what capabilities or background did make your success possible? Do you consider yourselves mathematicians, or at least strong with math?

[MC] I am certainly not a mathematician – I have engineering level skill. I consider Martin Piotte to have an exceptional mathematical mind (he participated successfully in international math contests when he was a student) even though he never formally studied in that field. In the end, the mathematics used in this contest seem very complex, but are really rather simple. Compared to what most people think, this was more of an engineering contest than a mathematical contest [See Martin’s response below for elaboration on this central point. -Ed]. Also, I think that having a perhaps less in-depth but wider array of skills and knowledge helped us.

[ES] You’ve said, when first getting started, you learned many core strategies/techniques from the Netflix Prize discussion board. Did you do much reading or research elsewhere to ramp up?

[MC] Having started late in the competition, the forum was a good starting point as many avenues had already been explored and links had been posted to many interesting papers. In the end though, reading and getting a good understanding of the actual research papers was a very important step. The forum was also a place where people proposed new (sometimes far fetched) ideas; these ideas often inspired us to come up with our own creative innovations.

PAWS is a great place to meet, greet and do business and though it is 5 hours away I have too much homework to do and grade while at University of Tennessee ( for now)-

Here is a very interesting poll that they are carrying it is good to see conferences take feedback in such a transparent manner-

paws poll

The world of Predictive Analytics: It's back

PAWS 2009 is back with a slam dunk line up of sponsors, and keynote speakers.

The deadline for early bord registration ends on Sept 4.

What’s holding you back?


Predictive Analytics World Fall 2009

Includes breakfasts, lunches, priceless networking during coffee breaks, the PAW Reception, and full access to program sessions and sponsor expositions.

Early Bird Price
(July 1 – Sept 4)
Regular     Price

Two Day Pass
(Oct 20-21)

$1390 $1590

Predictive Modeling Methods Workshop
(Oct 22)

$795 $895

Putting Predictive Analytics to Work
(Oct 19)

$795 $895

Hands-On Predictive Analytics
(Oct 19)

$795 $895


Disclaimer- I have no monetary transactions with PAW conference but as a blog partner get access to interviews , book review or content.

Interview Eric Siegel, Phd President Prediction Impact

An interview with Eric Siegel, Ph.D.President of Prediction Impact, Inc. and founding chair of Predictive Analytics World.

Ajay- What does this round of Predictive Analytics World have —–which was not there in the edition earlier in the year.

Eric- Predictive Analytics World (pawcon.com) – Oct 20-21 in DC delivers a fresh set of 25 vendor-neutral presentations across verticals employing predictive analytics, such as banking, financial services, e-commerce, education, healthcare, high technology, insurance, non-profits, publishing, retail and telecommunications.

PAW features keynote speaker, Stephen Baker, author of The Numerati and Senior writer at BusinessWeek.  His keynote is described at www.predictiveanalyticsworld.com/dc/2009/agenda.php#day2-2

A strong representation of leading enterprises have signed up to tell their stories — speakers will present how predictive analytics is applied at Aflac, AT&T Bell South, Amway, The Coca-Cola Company, Financial Times, Hewlett-Packard, IRS, National Center for Dropout Prevention, The National Rifle Association, The New York Times, Optus (Australian telecom), PREMIER Bankcard, Reed Elsevier, Sprint-Nextel, Sunrise Communications (Switzerland), Target, US Bank, U.S. Department of Defense, Zurich — plus special examples from Anheuser-Busch, Disney, HSBC, Pfizer, Social Security Administration, WestWind Foundation and others.

To see the entire agenda at a glance: www.predictiveanalyticsworld.com/dc/2009/agenda_overview.php

We’ve added a third workshop, offered the day before (Oct 19), “Hands-On Predictive Analytics.  There’s no better way to dive in than operating real predictive modeling software yourself – hands-on.”  For more info: www.predictiveanalyticsworld.com/dc/2009/handson_predictive_analytics.php

Ajay- What do academics, corporations and data miners gain in this conference? list 4 bullet points for the specific gains.

Eric- A. First, PAW’s experienced speakers provide the “how to” of predictive analytics. PAW is a unique conference in its focus on the commercial deployment of predictive analytics, rather than research and development. The core analytical technology is established and proven, valuable as-is without additional R&D — but that doesn’t mean it’s a “cakewalk” to employ it successfully to ensure value is attained.  Challenges include data requirements and preparation, integration of predictive models and their scores into existing organizational systems and processes, tracking and evaluating performance, etc. There’s no better way to hone your skills and cultivate an informed plan for your organization’s efforts than hearing how other organizations did it.

B. Second, PAW covers the latest state-of-the-art methods produced by research labs, and how they provide value in commercial deployment. This October, almost all sessions in Track 2 are at the Expert/Practitioner-level.  Advanced topics include ensemble models, uplift modeling (incremental modeling), model scoring with cloud computing, predictive text analytics, social network analysis, and more.

PAW’s pre- and post-conference workshops round out the learning opportunities. In addition to the hands-on workshop mentioned above, there is a course covering core methods, “The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and Common Data Mining Mistakes” (www.predictiveanalyticsworld.com/dc/2009/predictive_modeling_methods.php) and a business-level seminar on decision automation and support, “Putting Predictive Analytics to Work” (www.predictiveanalyticsworld.com/dc/2009/predictive_analytics_work.php).

C. Third, the leading predictive analytics software vendors and consulting firms are present at PAW as sponsors and exhibitors, available to provide demos and answer your questions.  What do the predictive analytics solutions do, how do they compare, and which is best for your? PAW is the one-stop-shop for selecting the tool or solution most suited to address your needs.

D. Fourth, PAW provides a unique, focused opportunity to network with colleagues and establish valuable contacts in the predictive analytics industry.  Mingle, connect and hang out with professionals facing similar challenges (coffee breaks, meals, and at the reception).

Ajay- How do you balance the interests of various competing softwares and companies who sponsor such event?

Eric- As a vendor-neutral event, PAW’s core program of 25 sessions is booked exclusively with enterprise practitioners, thought leaders and adopters, with no predictive analytics software vendors speaking or co-presenting. These sessions provide substantive content with take-aways which provide value that’s independent of any particular software solution — no product pitches!  Beyond these 25 sessions are three short sponsor sessions that are demarcated as such, and, despite being branded, generally prove to be quite substantive as well.  In this way, PAW delivers a high quality, unbiased program.

Supplementing this vendor-neutral program, the room right next door has an expo where attendees have all the access to software and solution vendors they could want (cf. in my answer to the prior question regarding software vendors, above).

Here are a couple more PAW links:

For informative PAW event updates:

To sign up for the PAW group on LinkedIn, see:

Ajay- Describe your career in science including research that you specialize in. How would you motivate students today to go for science careers

Eric- Well, first off, my work as a predictive analytics consultant, instructor and conference chair is in the application of established technology, rather than the research and development of new or improved methods.

But the Ph.D. next to my name reveals my secret past as an “academic”. Pure research is something I really enjoyed and I kind of feel like I had a brain transplant in order to change to “real world work”. I’m glad I made the change, although I see good sides to both types of work (really, they’re like two entirely different lifestyles).

In my research I focused on core predictive modeling methods. The ability for a computer to automatically learn from experience (data really is recorded experience, after all), is the best thing since sliced bread. Ever since I realized, as a kid, that space travel would in fact be a huge pain in the neck, nothing in science has ever seemed nearly as exciting.

Predictive analytics is an endeavor in machine learning. A predictive model is the encoding of a set of rules or patterns or regularities at some level. The model is the thing output by automated, number-crunchin’ analysis and, therefore, is the thing “learned” from the “experience” (data).  The “magic” here is the ability of these methods to find a model that performs not only over the historical data on your disk drive, but that will perform equally well for tomorrow’s new situations. That ability to generalize from the data at hand means the system has actually learned something.

And indeed the ability to learn and apply what’s been learned turns out to provide plenty of business value, as I imagined back in the lab.  The output of a predictive model is a predictive score for each individual customer or prospect.  The score in turn directly informs the business decision to be taken with that individual customer (to contact or not to contact; with which offer to contact, etc.) – business intelligence just doesn’t get more actionable than that.

For the impending student, I’d first point out the difference between applied science and research science. Research science is fun in that you have the luxury of abstraction and are usually fairly removed from the need to prove near-term industrial applicability. Applied science is fun for the opposite reason: The tangle of challenges, although less abstract and in that sense more mundane, are the only thing between you and getting the great ideas of the world to actually work, come to fruition, and have an irrefutable impact.

Ajay- What are the top five conferences in analytics and data mining in your opinion in the world including PAW.

Eric- KDD – The leading event for research and development of the core methods behind the commercial deployments covered at PAW (“Knowledge Discovery and Data Mining”).

ICML – Another long-standing research conference on machine learning (core data mining).

eMetrics.org – For online marketing optimization and web analytics

Text Analytics Summit – Text mining can leverage “unstructured data” (text) to augment predictive analytics; the chair of this conference is speaking at PAW on just that topic: www.predictiveanalyticsworld.com/dc/2009/agenda.php#day2-15

Predictive Analytics World, the business-focused event for predictive analytics professionals, managers and commercial practitioners – focused on the commercial deployment of predictive analytics: pawcon.com

Ajay- Would PAW 2009 have video archives, videos as well or podcasts for people not able to attend on site.

Eric- While the PAW conferences emphasize in-person participation, we are in the planning stages for future webcasts and other online content. PAW’s “Predictive Analytics Guide” has a growing list of online resources: www.predictiveanalyticsworld.com/predictive_analytics.php

Ajay- How do you think social media marketing can help in these conferences.

Eric- Like most events, PAW leverages social media to spread the word.

But perhaps most pertinent is the other way around: predictive analytics can help social media by increasing relevancy, dynamically selecting the content to which each reader or viewer is most likely to respond.

Ajay- Do you have any plans to take PAW more international? Any plans for a PAW journal for trainings and papers.

Eric- We’re in discussions on these topics, but for now I can only say, stay tuned!


The president of Prediction Impact, Inc., Eric Siegel is an expert in predictive analytics and data mining and a former computer science professor at Columbia University, where he won awards for teaching, including graduate-level courses in machine learning and intelligent systems – the academic terms for predictive analytics.He has published 13 papers in data mining research and computer science education, has served on 10 conference program committees, has chaired a AAAI Symposium held at MIT, and is the founding chair of Predictive Analytics World.

For more on Predictive Analytic World-

Predictive Analytics World Conference
October 20-21, 2009, Washington, DC
LinkedIn Group: www.linkedin.com/e/gis/1005097

PAW Blog Partner and 15 % off for you


Dear Readers,

If you plan to attend Predictive Analytics World ( Oct20-21) in Washington DC,

Here are the speakers – source

Speakers Washington DC 2009:

Stephen L. Baker, Senior writer, BusinessWeek

Stephen L. BakerStephen L. Baker, author of The Numerati, is a senior writer at BusinessWeek, covering technology. Previously he was a Paris correspondent. Baker joined BusinessWeek in March, 1987, as manager of the Mexico City bureau, where he was responsible for covering Mexico and Latin America. He was named Pittsburgh bureau manager in 1992. Before BusinessWeek, Baker was a reporter for the El Paso Herald-Post. Prior to that, he was chief economic reporter for The Daily Journal in Caracas, Venezuela. Baker holds a bachelor’s degree from the University of Wisconsin and a master’s from the Columbia University Graduate School of Journalism. He blogs at TheNumerati.net and Blogspotting.net, and can be found on Twitter at @stevebaker.

John F. Elder, Ph.D., CEO and Founder, Elder Research, Inc.

Dr. John F. ElderDr. John F. Elder heads a data mining consulting team with offices in Charlottesville, Virginia and Washington DC. Founded in 1995, Elder Research, Inc. focuses on scientific and commercial applications of pattern discovery and optimization, including stock selection, image recognition, text mining, biometrics, drug efficacy, credit scoring, cross-selling, investment timing, and fraud detection.

John obtained a BS and MEE in Electrical Engineering from Rice University, and a PhD in Systems Engineering from the University of Virginia, where he’s an adjunct professor, teaching Optimization or Data Mining. Prior to 13 years leading ERI, he spent 5 years in aerospace defense consulting, 4 heading research at an investment management firm, and 2 in Rice’s Computational & Applied Mathematics department.

Dr. Elder has authored innovative data mining tools, is active on Statistics, Engineering, and Finance conferences and boards, is a frequent keynote conference speaker, and is General Chair of the 2009 Knowledge Discovery and Data Mining conference in Paris. John’s courses on data analysis techniques – taught at dozens of universities, companies, and government labs – are noted for their clarity and effectiveness. Dr. Elder was honored to serve for 5 years on a panel appointed by the President to guide technology for National Security. His book on Practical Data Mining, with Bob Nisbet and Gary Minor, will appear in May 2009.

Usama Fayyad, Ph.D., CEO, Open Insights

Dr. Usama FayyadDr. Usama Fayyad was until recently Yahoo!’s Chief Data Officer and Executive Vice President of Research & Strategic Data Solutions where he was responsible for Yahoo!’s global data strategy, architecting Yahoo!’s data policies and systems, prioritizing data investments, and managing the Company’s data analytics and data processing infrastructure. Fayyad also founded and oversaw the Yahoo! Research organization with offices around the world. Yahoo! Research is building the premier scientific research organization to develop the new sciences of the Internet, on-line marketing, and innovative interactive applications.

Prior to joining Yahoo!, Fayyad co-founded and led the DMX Group, a data mining and data strategy consulting and technology company that was acquired by Yahoo! in 2004. In early 2000, he co-founded and served as CEO of Revenue Science, Inc.(digiMine, Inc.), a data analysis and data mining company that built, operated and hosted data warehouses and analytics for some of the world’s largest enterprises in online publishing, retail, manufacturing, telecommunications and financial services. The company today specializes in Behavioral Targeting and advertising networks. Fayyad’s professional experience also includes five years spent leading the data mining and exploration group at Microsoft Research and building the data mining products for Microsoft’s server division. From 1989 to 1996 Fayyad held a leadership role at NASA’s Jet Propulsion Laboratory (JPL), where his work in the analysis and exploration of scientific databases gathered from observatories, remote-sensing platforms and spacecraft garnered him the top research excellence award that Caltech awards to JPL scientists, as well as a U.S. Government medal from NASA.

Fayyad earned his Ph.D. in engineering from the University of Michigan, Ann Arbor (1991), and also holds BSE’s in both electrical and computer engineering (1984); MSE in computer science and engineering (1986); and M.Sc. in mathematics (1989). He has published over 100 technical articles in the fields of data mining and Artificial Intelligence, is a Fellow of the AAAI and a Fellow of the ACM, has edited two influential books on the data mining and launched and served as editor-in-chief of both the primary scientific journal in the field of data mining and the primary newsletter in the technical community published by the ACM: SIGKDD Explorations.

Eric Siegel, Ph.D., Conference Chair

Eric SiegelThe president of Prediction Impact, Inc., Eric Siegel is an expert in predictive analytics and data mining and a former computer science professor at Columbia University, where he won awards for teaching, including graduate-level courses in machine learning and intelligent systems – the academic terms for predictive analytics. After Columbia, Dr. Siegel co-founded two software companies for customer profiling and data mining, and then started Prediction Impact in 2003, providing predictive analytics services and training to mid-tier through Fortune 100 companies.

Dr. Siegel is the instructor of the acclaimed training program, Predictive Analytics for Business, Marketing and Web, and the online version, Predictive Analytics Applied. He has published 13 papers in data mining research and computer science education, has served on 10 conference program committees, and has chaired a AAAI Symposium held at MIT.

you can register at http://www.predictiveanalyticsworld.com/register.php

Here is the pricing

Predictive Analytics World Fall 2009

Includes breakfasts, lunches, priceless networking during coffee breaks, the PAW Reception, and full access to program sessions and sponsor expositions.

Super Early Bird Price
(till June 30)
Early Bird Price
(July 1 – Sept 4)
Regular     Price

Two Day Pass
(Oct 20-21)

$1190 $1390 $1590

Predictive Modeling Methods Workshop
(Oct 22)

$695 $795 $895

Putting Predictive Analytics to Work
(Oct 19)

$695 $795 $895

The discount code I can distribute to you  readers is the following: BLOGDC09 (15% off a two-day pass).You can do the maths…

(Ajay- Nopes I dont get money at all in these activities as blasted by some people
- but I do hope to get some good karma. Have a good time and book now).

PAW is back

The Predictive Analytics world is going to be back in October soon , and all those who missed out the stelar event can start booking now.

Here is the official BR ( blog Release)

Source: http://www.predictiveanalyticsworld.com/blog/wp-trackback.php?p=20

June 5th 2009 10:46 am

Keynotes at October’s PAW: Stephen Baker and Usama Fayyad

Predictive Analytics World, coming October 20-21 to Washington DC, has a great line-up of keynote speakers:

Stephen Baker, author of The Numerati and senior writer at BusinessWeek, where he’s been since 1987. Steve’s book has received a tremendous amount of attention this year. It is a revealing and insightful exploration of the opportunities and pitfalls of applied analytics, and consumer perception thereof.

Usama Fayyad, Ph.D. — CEO, Open Insights and formerly Yahoo!’s Chief Data Officer and Executive Vice President of Research & Strategic Data Solutions. Dr. Fayyad will return as an acclaimed keynote speaker. His keynote at February’s PAW (San Francisco) received extremely strong ratings from conference attendees.

Finally, Eric Siegel, Ph.D., will be kicking off PAW with a reprise of his keynote, “Five Ways to Lower Costs with Predictive Analytics.”

Teratec : High Performance Computing Event

Here is a good HC event.

The Ter@tec’09 Forum
June 30 and July 1st, 2009, Supélec (91- France)

Incidently it is also quite close to KDD conference http://www.decisionstats.com/2009/06/19/conference-of-the-year-kdd-2009/

High performance Simulation and Computing for competitiveness, innovation and employment

© Ter@tec 2008 CEA

The international HPC event
The  Ter@tec annual Forum, created in 2006, is a major occasion of meetings, exchanges and reflection in the field of high performance simulation and computing.

Since the success of its first edition, the Ter@tec Forum has developed and is now organized on two days with plenary conferences, workshops and exhibition.

In 2008, more than 400 international attendees, from research and industry, providers and users, met to review the largest worldwide programs and discuss the perspectives and the major challenges we are facing, both on the technology side and on the user side.

The Forum was recognized as very successful, with high-level presentations and workshops, and the personal participation of Mrs Valérie Pécresse, French Minister for Higher education and Research and Mr Janez PotoČnik, European Commissioner for Science and Research.

Ter@tec 2009, the meeting of the HPC community around the technological and economical aspects of the high performance simulation and computing development.

Source- http://www.teratec.eu/gb/forum/index.html

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