Machine Learning Times
Machine Learning Times

1 year ago
A Brief History of Predictive Analytics World


2019 marked the 10-year anniversary of the Predictive Analytics World conference series. During this decade-long run leading the commercial deployment of machine learning, PAW delivered value to over 14,000 attendees across more than 60 industry-leading events that have included over 1,200 sessions, internationally.

The field of machine learning has come a long way, and PAW has grown and adapted right along with it. In fact, the many cross-industry PAW events have helped catalyze and solidify the field, following predictive analytics from a nascent industry to the commercial movement it is today.

Check out these historical PAW milestones, from spawning the Target-predicting-pregnancy publicity debacle, to getting dinged by the Hollywood action movie star Chuck Norris, to growing into the leading international event series it is today.

February 2009: The inaugural Predictive Analytics World.

The first PAW was held in San Francisco as a two-track event. It blazed the trail as the very first vendor-neutral conference focused on machine learning’s commercial deployment– in comparison with existing academic or vendor-run conferences at the time – and remains the leading such event.

October 2010: PAW spawns the Target-predicting-pregnancy story.

A PAW keynote from Target on predicting customer pregnancy (see the full session video here) spawned a publicity debacle for the large retailer, which took place more than a year later in early 2012, by way of a front-page New York Times Magazine article by Charles Duhigg – an excerpt that served to publicize the launch of his book “The Power of Habit” at the time – which expounded upon the keynote’s contents and was regurgitated by a media frenzy. However, this flame-igniting article probably misled the public about the reality behind an alleged anecdote involving a pregnant teenager.

November 2010: PAW begins holding annual events in London.

September 2011: Predictive Analytics World for Government launches in Washington, DC.

March to October 2012: PAW begins holding three main business events per year in the U.S.: East coast, west coast, and Chicago.

November 2012: PAW begins holding annual events in Germany.

February 2013: Eric Siegel’s book, “Predictive Analytics”.

The first edition of PAW Founder Eric Siegel’s book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, publishes in the U.S. It will be used in courses at over 35 universities, rank as the #1 Amazon bestseller in 2 categories, and be translated into 12 languages. The updated edition was released in 2016.

March 2014The Predictive Analytics Times news site launches as an informative sister property to the PAW events.

April 2013: Chuck Norris writes about Predictive Analytics World.

Famed Hollywood action film star Chuck Norris mentioned PAW in a derogatory manner in an article expressing privacy concerns over the IRS’s collection of social media data, as covered by a speaker from the IRS at PAW Government.

June 2014: PAW for Manufacturing (now PAW Industry 4.0) begins as an annual event.

September 2014PAW for Healthcare begins as an annual event.

October 2016PAW for Financial Services begins as an annual event.

February 2017: PAW Industry 4.0 begins also as a repeated event in Germany.

June 2018: Deep Learning World launches as an annual sister event in Vegas.

November 2018: Deep Learning World also begins as an annual event in Germany.

September 2019: PAW Government changes its name to Data Driven Government.

June 2020: Mega-PAW changes its name to Machine Learning Week, still made up of five co-located conferences: PAW Business, PAW Financial, PAW Industry 4.0, PAW Healthcare, and Deep Learning World.

Noteworthy Speakers and Keynotes

Along the way, PAW audiences have enjoyed guidance and inspiration from a stellar range of keynote speakers from the likes of Google, Lyft, Uber, Facebook, UPS, Verizon, HP, IBM, FICOAmazonMetLifeCharles Schwab, etc. – as well as the following sample of noteworthy keynote speakers:

John Elder, chair of Elder Research, the most widely experienced data consultancy in North America. An extremely popular speaker, author, and workshop instructor, John has spoken at the vast majority of PAW events, internationally, over the last decade.  He’s the chair of Data Driven Government (formerly PAW Government) and his firm also heads up the PAW Healthcare event, which is chaired by Elder Research’s Jeff Deal.

Dean Abbott, the founding chief data scientist of SmarterHQ. Previously a leading “rock star” consultant, Dean is famed for his fluency with more machine learning tools than any other practitioner we know. Like John Elder, Dean is an extremely popular speaker and workshop instructor who’s participated at the vast majority of PAW events, internationally — these two speakers are easily the two most frequent speakers, far surpassing even the frequency of PAW Founder Eric Siegel.

Karl Rexer, founder of Rexer Analytics, a leading boutique consulting firm in predictive analytics. Karl is a a frequent plenary speaker who often presents on his firm’s well-regarded, industry-standard Data Scientist Survey. His firm has completed projects for an impressively diverse portfolio of clients.

  • David Gondek, who led the design of machine learning integration for IBM’s Jeopardy champion computer, Watson. Watson’s triumph on this TV quiz show is one of the top few bullets in the history of machine learning.
  • Thomas Davenport, president’s distinguished professor Babson College and co-author, “Competing on Analytics.” This famed thought leader is known for his insight and gravitas.
  • Roger Craig, an analytics expert who used this technology to guide his own study to compete on the TV quiz show Jeopardy, thereby setting many records on the show, including the highest one day winning total ever and the fourth highest overall total ever.
  • Usama Fayyad, former chief data officer of both Yahoo! and Barclays.
  • Anthony Goldbloom, CEO and founder of the renowned data science competition facilitator Kaggle.
  • Stephen Baker, author of “The Numerati” and senior writer at BusinessWeek.
  • Obama for America 2012 campaign’s Daniel Porter and Rayid Ghani, who served as director of statistical modeling and chief data scientist, respectively.
  • Brett Goldstein, the chief data officer of the City of Chicago.
  • Christopher Wiggins, Columbia professor and chief data scientist of The New York Times.


Machine Learning Week Is Born

June 2018: The first Mega-PAW event (now Machine Learning Week) – five co-located events in Vegas.

Predictive Analytics World in North America continued its growth trajectory by bringing together all industry-specific PAW events in Las Vegas. Convening all the key industry figures and verticals greatly expands the networking potential. The wide range of jointly scheduled events includes: PAW BusinessPAW FinancialPAW Industry 4.0 (formerly PAW Manufacturing), PAW Healthcare, and Deep Learning World,

June 2018Deep Learning World launches as an annual sister event in Vegas.

November 2018: Deep Learning World also begins as an annual event in Germany.

Deep Learning World covers deep learning’s commercial deployment across industry sectors. This relatively new form of neural networks has blossomed, both in buzz and in actual value, scaling machine learning to process, for example, complex image data.


Onward and Upward: Machine Learning Week Vegas 2020

In 2020, there will be only one Machine Learning Week (formerly Mega-PAW): May 31 – June 4, 2020, at Caesars Palace, Las Vegas. With 2018’s first-ever Machine Learning Week being a stunning success, this new multi-event format continues in 2020 as a regular annual event. By design, this mega-conference is where to meet the who’s who and keep up on the latest techniques, making it the leading machine learning event that excites and unites. Machine Learning Week brings together five co-located events:

… plus a range of full-day training workshop options that include two on deep learning and TensorFlow, as well as RSpark, and advanced topics such as ensemble models and other advanced techniques.

Cross-registration options are available so you can pick and choose which parts of this seven-track mega-event are right for you. Register now to secure the early bird rates.

About the Author

Eric Siegel, Ph.D., founder of the Predictive Analytics World and Deep Learning World conference series and executive editor of The Predictive Analytics Times, makes the how and why of predictive analytics (aka machine learning) understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, the host of The Dr. Data Show web series, a former Columbia University professor, and a renowned speaker, educator, and leader in the field. Read also his articles on data and social justice and follow him at @predictanalytic.


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