Predictive Analytics World London, the leading vendor-neutral machine learning conference, is holding its tenth annual conference this October 16-17 in London, UK at etc.venues, 200 Aldersgate. Join PAW London to hear top practitioners describe the design, deployment and business impact of their machine learning projects.
Background of Predictive Analytics World
Predictive Analytics World is the premier cross-vendor conference for machine learning and predictive analytics professionals, managers and commercial practitioners. This conference delivers case studies, expertise and resources to achieve:
Bigger wins: Strengthen the impact of predictive analytics deployment
Broader capabilities: Establish new opportunities in data science and machine learning
Big data: Leverage bigger data for prediction and drive bigger value
The only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, manufacturing, high technology, insurance, non-profits, publishing, and retail.
Why bring together such a wide range of endeavors? No matter how you use predictive analytics, the story is the same: Predictively scoring customers, employees, students, voters, patients, equipment, and other organizational elements optimizes performance. Predictive analytics initiatives across industries leverage the same core predictive modeling technology, share similar project overhead and data requirements, and face common process challenges and analytical hurdles.
What will I learn at Predictive Analytics World?
New apps: New ways to apply predictive analytics.
Do better: How to achieve better results with predictive analytics.
Companies: What companies are at the leading edge of predictive analytics and what are they doing?
Solutions: Which are the best predictive analytics solution providers, what do they do and how do they compare?
Colleagues: Who are my colleagues facing the same challenges as I and how can we work together?
Resources: What other resources are available?
Who is Predictive Analytics World for?
PAW attendees range across verticals and across enterprise functions.
No matter what your role in or relationship to predictive analytics projects, you will find value in the sessions, case studies and networking available at Predictive Analytics World.
Managers. Project leaders, directors, CXOs, vice presidents, investors and decision makers of any kind involved with analytics, direct marketing or online marketing activities.
Marketers. Personnel running or supporting direct marketing, response modeling, or online marketing who wish to improve response rates and increase campaign ROI for retention, upsell and cross-sell.
Technology experts. Analysts, data scientists, BI directors, developers, DBAs, data warehousers, web analysts, and consultants who wish to extend their expertise to predictive analytics.
Big data and data science
Predictive analytics is central to the big data and data science movements. The ultimate use of data is to learn from it to predict. Focusing on data or how much of it there is can overlook this point. What is the value, the function, the purpose? The most actionable win from data — to more effectively drive organizational operations — is prediction.
Machine learning
Predictive analytics means the commercial deployment of machine learning (the two terms are often used synonymously). Although the term “machine learning” used to be common only within the walls of research labs, it’s now also used more and more in the context of commercial deployment. Whichever term you prefer, we are discussing technology that learns from data to predict or infer an unknown, including decision trees, logistic regression, neural networks, and many others.
Experts and newcomers
Predictive Analytics World covers all the bases for both expert practitioners as well as newcomers. As the universal, cross-vendor meeting place that brings together the who’s who of predictive analytics, PAW presents not only unique opportunities to gain knowledge, but the industry’s premier networking event.
Get started
If you’re new to predictive analytics, kicking off a new initiative, or exploring new ways to position it at your organization, there’s no better place to get your bearings than Predictive Analytics World. See what other companies are doing, witness vendor demos, participate in discussions with the experts, network with your colleagues and weigh your options!
Valuable colleagues
Mingle, network and hang out with your best and brightest colleagues. Exchange experiences over lunch, breaks and the conference reception, connecting with those professionals who face the same challenges as you.
Predictive Analytics World — the facts:
0
Years
0
Locations
0
Total Events
0
Speakers
0
Sessions
0
Companies
Impressions from PAW London
Testimonials
Read what attendees think about Predictive Analytics World
Ben Rollins
- Global Advanced Analytics Specialist
Bain & Company
“The PAW business conference is a great way to meet peers within the industry and to see what everybody else is doing to make sure you don’t fall behind.”
Emre Yayıcı
- Managing Partner
Analytics Center
„The agenda/ content and operations were both handled very professionally. As a person attending to many conferences (and also as an organizer), I can say that this is rare. Thanks for all!“
Rainish Lalai
- Senior Analytics Specialist
Etihad Airways
“An excellent conference with high-quality speakers, the right companies partnered, and overall a very knowledgable experience.”
Silvan Rath
- Founder
predict.io
„PAW was a phenomenal event. Packed with actual practitioners. And none of the typical „hurray“ presentations from vendors trying to sell you up. Really enjoyed the vibe.“
Hector Leads a team at Google AI: Healthcare (formerly a part of Google Brain) researching the applications of AI on Medical Waveforms. His other Google projects include image search ranking, perception for the self-driving car, video content analysis and Youtube’s Emmy award winning personalized video recommendation system.
Dr Saúl Vargas Sandoval is a Senior Data Scientist in ASOS, the U.K.’s largest online-only fashion retailer. His current work focuses on designing and adapting recommendation algorithms to help customers discover clothes. Saúl has a PhD from the Autonomous University of Madrid (Spain) on the topic of novelty and diversity in recommender systems, and has previously applied his skills in both academia (University of Glasgow) and industry (Mendeley).
Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and head of Skymind Labs the Machine Learning research lab affiliated with DeepLearning4J. He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters of Science in Data Science degree and oversaw the company’s transformation from co-working space to Data Science organization. Mike began his career in academia serving as a mathematics teaching fellow for Columbia University before teaching at the University of Pittsburgh. His early research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.
Abhishek Joshi ‘AJ’ is a Sr. Director in Visa’s consulting & analytics group. He is responsible for helping financial institutions with improving growth and profitability through advanced analytics techniques. AJ has diverse experience in employing analytics to solve business problems across multiple industries – Manufacturing & Engineering, Financial Services and Telecom.
Bas Geerdink is responsible for the fast data systems that process and analyze streaming data at ING. He has a background in software development, design, and architecture with broad experience from C++ to Prolog to Scala. He studied artificial intelligence and informatics and has published research on reference architectures for big data solutions.
Joey Marburger was labeled as The Washington Post’s punk rock star by Digiday for the work he’s accomplished as Director of Product. During his time at The Post, there has been immense growth which Columbia Journalism Review called a ‘revolution.’ Most recently, Fast Company placed him at number 13 on their Most Creative People in Business 2017 list.
Marburger leads a team of product designers and managers overseeing the development and design of digital products such as washingtonpost.com, Android and iOS apps, distributed news, and a variety of other platforms. He has been at The Post for more than eight years, moving from Mobile Design Director to Director of Digital Products and Design to his current role. He has also worked at Gannett and the Indianapolis Star.
He lives in Northeast D.C. with his wife, Cas, the social media manager for the Truth Initiative Foundation, and their black Labrador retriever, Walt.
The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques
Intended Audience: Interested in the fundamentals of modern machine learning techniques.
Knowledge Level: For this introductory-level workshop, it is helpful for attendees to already be familiar with the basics of probability and coding.
Workshop Description
This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning).
Predictive analytics has proven capable of generating enormous returns across industries – but, with so many machine learning modeling methods, there are some tough questions that need answering:
How do you pick the right one to deliver the greatest impact for your business, as applied over your data?
What are the best practices along the way?
How do you make it sure it works on new data?
In this workshop, renowned practitioner and hugely popular instructor Dr. John Elder will describe the key inner workings of leading machine learning algorithms, demonstrate their performance with business case studies, compare their merits, and show you how to select the method and tool best suited to each predictive analytics project.
Attendees will leave with an understanding of the most popular algorithms, including classical regression, decision trees, nearest neighbors, and neural networks, as well as breakthrough ensemble methods such as bagging, boosting, and random forests.
This workshop will also cover useful ways to visualize, select, reduce, and engineer features – such as principal components and projection pursuit. Most importantly, Dr. Elder reveals how the essential resampling techniques of cross-validation and bootstrapping make your models robust and reliable.
Throughout the workshop day, Dr. Elder will share his (often humorous) stories from real-world applications, highlighting mistakes to avoid.
If you’d like to become a practitioner of predictive analytics – or if you already are and would like to hone your knowledge across methods and best practices – this workshop is for you.
What you will learn:
The tremendous value of learning from data
How to create valuable predictive models with machine learning for your business
Best Practices, with real-world stories of what happens when things go wrong
Why Attend?
View Dr. Elder describing his course, “The Best of Predictive Analytics,” in this brief video:
Schedule
Workshop starts at 9:00am
Morning Coffee Break at 10:30am – 11:00am
Lunch provided at 12:30pm – 1:15pm
Afternoon Coffee Break at 3:00pm – 3:30pm
End of the Workshop: 5:00pm
Coffee breaks and lunch are included.
Instructor
Dr. John Elder, Founder and Chair, Elder Research
John Elder leads America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Washington DC, Maryland, and North Carolina. Dr. Elder co-authored books on data mining, ensembles, and text mining — two of which won book-of-the-year awards. John was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. Dr. Elder is an (occasional) Adjunct Professor of Engineering at UVA, and was named by President Bush to serve 5 years on a panel to guide technology for national security.
Introduction to Artificial Intelligence for Marketing
From market research to direct mail metrics to web analytics to Big Data, the job of “marketing” has changed dramatically over time. We have arrived at a fundamental shift in marketing that is as impactful as the advent of the Internet: Artificial Intelligence and Machine Learning.
This workshop introduces marketing professionals of all ranks to the theory, the language and the practical application of these disruptive technologies.
This workshop will not teach you how to be a data scientist.
It will teach you enough about the language and implications to speak cogently with your colleagues, and determine where to apply this innovative technology first. You will also get a firm grasp on how these new tools will change your job and what you can do to remain relevant in tomorrow’s marketing department.
Key Takeaways
How Machine Learning Works for Marketing
What Machine Learning Cannot do for Marketing
How to Onboard AI and ML into Your Organization
This workshop is for marketing professionals who are comfortable consuming analytics outputs, but must now face a new, educational learning curve.
This workshop is for data scientists to help them understand the problem the marketing department is trying to solve and the available data sets.
This workshop is for marketing managers who must respond to the C-level insistence that the marketing department “get with the times” (management by in-flight magazine).
This workshop is for those who need to survive in these changing times even though they are not data scientists, algorithm magicians, or predictive analytics statisticians.
Each participant will receive a copy of Jim’s twelfth book:
Instructor
Jim Sterne, Founder, eMetrics Summit
Jim Sterne has been in data processing since 1979, an online marketing consultant since 1993, and an online marketing analytics consultant since 2000. Sterne focuses on proving the value of digital communication as a medium for creating and strengthening customer relationships. He is the founding president of the Digital Analytics Association and producer of the eMetrics Summits. Sterne was named one of the 50 most influential people in digital marketing by the United Kingdom’s premier interactive marketing magazine and one of the top 25 Hot Speakers by the National Speakers Association, to which he credits his degree in Shakespeare. He has consulted to some of the world’s largest companies; lectured at MIT, Stanford, USC, Harvard, and Oxford; and sat on a plane to Las Vegas grading the CRM strategy plans of a Nigerian mobile phone company for a course he taught in Singapore produced by a training company in Shanghai. Sterne is the author of 15 books on online marketing and analytics including his latest, “Artificial Intelligence for Marketing: Practical Applications” (Wiley, August, 2017)
Dr. David Stephenson is an independent consultant in the field of data science and big data analytics and author of the forthcoming Pearson publication, “Big Data Demystified: How to make better business decisions”. He has led global analytics programs for companies such as eBay, Axel Springer and Coolblue (a skyrocketing ecommerce player in the Netherlands) and has worked extensively in insurance, capital markets, and financial risk management. He has also served as an expert advisor to top-tier investment, private equity and management consulting firms.
David completed his Ph.D. at Cornell University and was subsequently Professor at the University of Pennsylvania, teaching applied analytics to graduate students in the engineering and Wharton business schools.
David is currently based in Amsterdam.
Predictive Analytics World is London’s leading vendor independent conference for data science practitioners. Now in its tenth year, the conference brings together data science and machine learning practitioners from around the globe, representing a broad spectrum of industries. Some sessions will be technical, some visionary and strategic, and some focusing on operational learnings, but all are presented with the goal of helping attendees become better data scientists, regardless of what software or hardware they use.
Conference covers topics such as
Machine learning methods for marketing
Explainable AI
Maximizing business impact from small analytics teams
Deep learning: Generative Adversarial Methods, Reinforcement learning, and more
Data science staffing
Maximizing the effectiveness of analytics programs
Predictive analytics optimizes marketing campaigns and website behavior to increase customer responses, conversions and clicks, and to decrease churn. Each customer’s predictive score informs actions to be taken with that customer — business intelligence just doesn’t get more actionable than that.
Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model which has, in turn, been trained over your data, learning from the experience of your organization.
Is predictive analytics different from forecasting?
Predictive Analytics World London often include select sessions on forecasting since it is a closely related area, and, in some cases, predictive analytics is used as a component to build a forecast model.
However, Predictive analytics is something else entirely, going beyond standard forecasting by producing a predictive score for each customer or other organizational element. In contrast, forecasting provides overall aggregate estimates, such as the total number of purchases next quarter. For example, forecasting might estimate the total number of ice cream cones to be purchased in a certain region, while predictive analytics tells you which individual customers are likely to buy an ice cream cone.
Is this a “machine learning” conference?
Yes. Predictive analytics means the commercial deployment of machine learning (the two terms are often used synonymously). Although the term “machine learning” used to be common only within the walls of research labs, it’s now also used more and more in the context of commercial deployment. Whichever term you prefer, we are discussing technology that learns from data to predict or infer an unknown, including decision trees, logistic regression, neural networks, and many other methods.
Is this a “data mining” conference?
Yes. Data mining is often used synonymously with predictive analytics, and, in any case, predictive analytics is a type of data mining.
Is this a “data science” conference?
Yes. Predictive analytics is a form of data science. Moreover, it is the most actionable form. A predictive model generates a predictive score for each individual, which in turn directly informs decisions for that individual, e.g., whether to contact, extend a retention offer, approve for credit, investigate for fraud, or apply a certain medical treatment. Rather than solely providing insights, predictive analytics directly drives or informs millions of operational decisions.
Is this a “big data” conference?
Yes. Predictive analytics is a key method to truly leverage big data. At the center of the big data revolution is prediction. The whole point of data is to learn from it to predict. What is the value, the function, the purpose? Predictions drive and render more effective the millions of organizational operational decisions taken every day.
Is this an AI conference?
Yes. Artificial intelligence (AI) is a broad, subjective term with many possible definitions—but by any definition, it always includes machine learning (predictive modeling) as an example of AI technology/capabilities.
Is Predictive Analytics World run by a software vendor?
No. Predictive Analytics World provides a balanced view of predictive analytics methods and tools across software vendors and solution providers.
Is Predictive Analytics World a research conference?
No. Predictive Analytics World is focused on today’s commercial deployment of predictive analytics, rather than academic or R&D activities. Separately, there are a number of research-oriented conferences; in predictive analytics’ commercial application, we are essentially standing on the shoulders of those giants known as researchers.
Are you considering new speakers for Predictive Analytics World?
For speaker information and proposal submissions, click here.
Ready to attend?
Register now for Predictive Analytics World London
