Better Decisions= Faster Stats
I just got an email from the great Dr Eric Siegel, one of my many mentors in this field of learning analytics and data. There are just three more days left for the Early Bird Price- so if you are doing your Media Planning Budget – it is a good time to register here. You can click on the screenshot itself to go to Registration Page.
Conference :Message on Linkedin groupof Decisionstats
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Predictive Analytics World, Feb 16-17 in San Francisco
The agenda for Predictive Analytics World – Feb. 16-17 2010 in San Francisco – has been posted: http://www.pawcon.com/sanfrancisco/2010/agenda_overview.php
February’s PAW covers hot topics and advanced methods such as social data, uplift modeling (net lift), text mining, massively parallel analytics, in-cloud deployment, and innovative applications that benefit organizations in new and creative ways.
Be sure to register by December 18 for the Super Early Bird to save $400 off the Regular Price:
http://www.predictiveanalyticsworld.com/register.phpAnd take an additional $50 off the Super Early Bird with discount code: LIN150
Below is some more info – let me know if you have any questions.
-Eric Siegel, Conference Chair
———–
PAW-2010 includes 25 sessions across two tracks, so you can witness how predictive analytics is applied at 1-800-FLOWERS, Amazon.com, AT&T, BBC, Canadian Automobile Association, Charles Schwab, Continental Airlines, Deutsche Postbank, Google, Group RCI, IBM, PASSUR Aerospace, PayPal (eBay), Sun Microsystems, U.S. Army, Visa, Walmart Financial Services, and Younoodle, plus special examples from the U.S. government agencies CBP, NCMI, NGIC, NSA, and SSA.
Keynote speakers include Kim Larsen, Director Advanced Analytics at Charles Schwab, Andreas S. Weigend, Ph.D., Former Chief Scientist at Amazon.com, and Program Chair Eric Siegel, Ph.D., President of Prediction Impact and former Columbia University professor.
Predictive Analytics World is the business-focused event for predictive analytics professionals, managers and commercial practitioners, covering today’s commercial deployment of predictive analytics, across industries and across software vendors.
For more information, including three pre- and post-event workshops:
http://www.predictiveanalyticsworld.com
Here is an interview with Stephen Baker, the author of the famous and remarkable book The Numerati. Stephen is the senior editor at Businessweek and his remarkable book made the world sit up and pay attention because for the first time, anyone wrote of the increasingly quant driven lives we lead thanks to the internet and the analytical brains that power the stimulus, design and targeting of it. Increasing amounts of data is collected about consumers than at any previous point of time in human history and the number crunchers or the quant jocks are the ones who increasingly help with decision making and decision management. Steve calls these people “The Numerati” or the new math people who help shape our lives.
There will always be lawyers and financiers who make loads of money. But they will have quantitative experts on their teams- Stephen L Baker
Ajay- Describe your career journey from high school to a technology writer to author of The Numerati.
Steve- I was always interested in history and in literature, and in college I fell in love with Spanish. So after college, I moved to Ecuador, taught English, and wrote fiction. I saw early on that I wasn’t going to be able to make a living with fiction. So I went into journalism. My goal was to become a correspondent in Latin America. Through my 20s, I worked in Vermont, Madrid, Argentina, Venezuela, Washington DC, and El Paso, Texas. And I finally got the job I was looking for, bureau chief for the Mexico bureau of BusinessWeek magazine.
After Mexico, my family and I moved to Pittsburgh. It appeared that the magazine was losing interest in heavy industry in the mid-90s, so I began to write about software and robotics coming out of at Carnegie Mellon University. That was my transition into technology. A year later, BusinessWeek offered me a job covering technology in Europe. I moved with my family to Paris, where we lived for four years. I focused largely on mobile communications. It seemed to me that the combination of mobility and the Internet would fundamentally change communications.
I returned to New York in 2002. I focused on big picture stories. One day in 2005, I proposed a story about the decline of the U.S. technology industry. I argued that we were behind in wireless and in broadband, we were graduating fewer scientists and engineers than other great powers, especially in Asia. One editor pointed out that mathematics was critical for these competitive issues. The editor in chief, Steve Adler, called for a cover story on math, and he assigned it to me. I didn’t know much about math at the time, and I still don’t. But this gave me the chance to dive into the world of data analysis. I wrote a cover story, Math will Rock Your Business, and later got the contract to write the Numerati.
Ajay- How do you think the government can motivate more American students to science careers?
Steve- I think focusing on the science that kids find cool–robotics, space and ocean exploration, would help. Funding basic research would be useful. But I don’t think it’s entirely a governmental issue. Parents, companies, universities, they all have to participate.
Ajay- What are the top tips you would give to aspiring technology writers and bloggers (like myself)?
Steve-
1) Learn about non tech subjects, such as history, literature, art and psychology
2) Work on writing clearly for non experts. Avoid jargon.
3) Do reporting
4) Do more reporting
Ajay-The Numerati portrays a math elite which breaks the stereotype of the lonely, nerdy geek. How important do you think is that common people be more educated in math so they are more aware of marketing operations and credit offers?
Steve- I think it’s important for common people, as you call them, to understand basic statistics. More and more of our lives are going to be analyzed and communicated to us statistically. Those who do not understand this will not know to ask the right questions, and will be easily fooled. This is also true within companies. CEOs can be fooled by numbers, just like anyone else.
Ajay- Asia delivers a disproportionate number of science graduates. Yet one generation ago American and European heritage scientists made the trip to the moon with very basic computers. As our lives get increasingly shaped by the Numerati, how important are geo-cultural influences in its membership?
Steve- Most of the Numerati I met in the United States were born outside the U.S. The US has long relied on foreign brains, especially for its technology industry. As the Numerati study people’s lives, the quantitative experts will increasingly need to work closely with linguists, anthropologists, and psychologists. And they’ll need to understand different global cultures and languages. In this sense, the international nature of the Numerati is an advantage.
Ajay- Do you think the shift in money and influence from lawyers and financiers to scientists and mathematicians is temporary or is it here to stay?
Steve-I think it’s here to stay. There will always be lawyers and financiers who make loads of money. But they will have quantitative experts on their teams.
Ajay- What influenced your decision to be associated with Predictive Analytics world?
Steve- I had the privilege of interviewing Eric Siegel as I was researching the book. We’ve kept in touch since then. I think he’s very bright and does excellent work.
Ajay- What does Stephen Baker do when not writing books or articles or observing the world go around him?
Steve- I like to ride bicycles, I like to travel. I love Spanish and French and baseball and music
Biography-
Stephen L. Baker is the author of The Numerati and 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.
You can read more about the Numerati at http://thenumerati.net/index.cfm?catID=18 Stephen L Baker is the keynote speaker at Predictive Analytics World and you can check the details here http://www.predictiveanalyticsworld.com/register.php if you want to listen to him at the event.
You can follow Steve on twitter at http://twitter.com/stevebaker and follow his blog here http://www.businessweek.com/the_thread/blogspotting/
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:
www.predictiveanalyticsworld.com/notifications.php
To sign up for the PAW group on LinkedIn, see:
www.linkedin.com/e/gis/1005097
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!
Biographyy
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
www.predictiveanalyticsworld.com
LinkedIn Group: www.linkedin.com/e/gis/1005097
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. 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. 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 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
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
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
|
$1190 | $1390 | $1590 |
Predictive Modeling Methods Workshop
|
$695 | $795 | $895 |
Putting Predictive Analytics to Work
|
$695 | $795 | $895 |
(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).
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