Intended Audience: Those interested in the workings and use of “the other kind of AI,” predictive AI.

Knowledge Level: Although this workshop assumes no prior knowledge of core predictive AI methods, it can be helpful for attendees to be familiar with some probability and coding.

Free Book! Each attendee will be reimbursed by the organizers for the cost of buying a copy of Dr Elder’s “Handbook of Statistical Analysis and Data Mining Applications 1st Edition” (up to $50, receipt required).

“I can’t remember when I walked away from a one-day training course so filled with insights and new ideas. Thank you for your real work experiences and great examples about analytics and modeling for decision making. Because of your training on modeling techniques, you helped me rethink my approach to data mining and predictive analytics. You were generous with your time and with the Q&A. I would like to learn more than just the basics you covered, but what I did learn gave me a foundation for better management techniques and using data analytics.”
Manager Data Analytics,
US Postal Service Office of Inspector General

Workshop Description

Despite today’s tremendous attention on genAI, most returns still come from “the other kind of AI,” predictive AI (aka predictive analytics). Predictive AI is the technology you turn to for improving your organization’s existing large-scale operations – whether for targeting marketing, risk management, fraud detection, predictive maintenance, or most any other primary function.

In a nutshell, predictive AI is: the enterprise application of machine learning algorithms (in contrast with genAI, which is the product of ML algorithms, after applying them over media in order to generate media). ML algorithms achieve something remarkable: They learn from prior outcomes (in the form of data) to deliver millions of predictions, which in turn directly inform operational decisions. In so doing, predictive AI uniquely complements genAI.

Many predictive AI fundamentals that you will learn during this workshop pertain to genAI as well. These include:

1. How to navigate the strengths and weaknesses of each analytical technique
2. How to understand the intrinsic relationship between the data and the resulting model – how data “shapes” the model
3. How to quantify AI performance and align with business value.

Digging Into Predictive AI

Predictive AI has delivered enormous returns across industries – over several decades – but, there are so many competing machine learning modeling methods to choose from, using these methods brings up some tough questions:

• 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 AI project.

Attendees will leave with an understanding of the most popular algorithms, including classical and constrained 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 input shuffling. Most importantly, Dr. Elder reveals how essential resampling techniques – such as cross-validation and Target Shuffling – 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 AI – 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
• How to solve the “Crisis of Science”, where most published results can’t be replicated
• 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 AI,” in this brief video:

Schedule

• Workshop starts at 8:30am
• AM Break from 10:00 – 10:15am
• Lunch Break from 12:00am – 12:45pm
• PM Break: 2:15 – 2:30pm
• End of the Workshop: 4:30pm

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, North Carolina, and London. 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.

More statements of testimony

“Best workshop I had attended in a long time. Business perspective is a big advantage of the workshop.”
Mandres Uribe-Sanchez
Liberty Mutual Insurance

“In depth knowledge of methods. Well structured presentation slides. Broad practice knowledge and advice. Presented in fun and humor.”
Ling Zhang
Comcast

“You don’t know what you don’t know … after this course, I now know what I don’t know and what I should develop greater understanding in for both myself, my company and our clients”

Sean Liddle
Deloitte
“Some very complex topics were explained very comprehensively and clearly, and put into a wider context of how to use these in real-life situations.”
Colin Styles
Information Architect
Sussex Health Informatics Service