The premier machine learning event –
select a conference:

PAW Healthcare
PAW Business
PAW Financial
Data Driven Government
PAW Industry 4.0
PAW Climate
Deep Learning World

The premier machine learning event –
select a conference:

PAW Business

PAW Government

PAW Financial

PAW Healthcare

PAW Industry 4.0
PAW Climate
Deep Learning World

Machine Learning Week is the leading cross-vendor conference series covering the commercial deployment of machine learning and predictive analytics.

Machine Learning Week — the facts:




Total Events







2023 Keynote Speakers

Bala Ganesh

William Wilkins
VP, Chief Risk and Analytics Officer
Safety National Casualty Corporation

Bala Ganesh

Gulrez Khan
Data Science Lead

Bala Ganesh

Terry Miller
Executive Director-Predictive Analytics (Global Services)
Johnson Controls

Bala Ganesh

Arnab Chakrabarti
Senior Research Scientist
Hitachi America

Bala Ganesh

Sami Ghoche
Cofounder & CTO

Bala Ganesh

Vanja Josifovski
CEO & Co-Founder

Bala Ganesh

Sarah Kalicin
Data Scientist

Bala Ganesh

Jen Gennai
Head of Responsible Innovation, Global Affairs

Bala Ganesh

Brandon Southern
Sr. Manager - Business Intelligence

Plus a special plenary session from:

Bala Ganesh

John Elder Ph.D.
Founder & Chair
Elder Research


Simon Padron, Senior Engineer - R&D, Parker Hannifin

Had an amazing week of great insights into the world of machine learning and deep learning at the Predictive Analytics World Conference. I leave with lots of notes and expanded knowledge into the latest state of the art methods.

Ymke de Jong, Program Lead - Data & AI, Philips

Great event with great people! Learned a lot. I am looking forward to bring our learnings into practice!

Darin Conti, Head of Commercial Predictive Analytics, S&P Global Market Intelligence

Machine Learning Week provides a great opportunity for analytics managers and teams early on in their ML journey to learn from experienced practitioners and gain actionable insights. In addition, there is a diversity of topics and sessions from which to choose and ample time to socialize/network with attendees.

John Crissman, Research Analyst, CNA Corporation

Machine Learning Week is the place to be if you want to learn current best practices and engage with industry leaders.

William Wilkins, VP, Chief Risk and Analytics Officer, Safety National Casualty Corporation

I like coming to the event since it caters not just to the practitioner, but those who need to help the practitioner demonstrate the value of the analytics products.

Anasse Bari, Ph.D., Associate Professor, New York University

Predictive Analytics World was excellent! The organization was phenomenal and the speakers were so interesting. Dr. Eric Siegel, the founder of PAW, is a visionary and a leader in the machine learning and predictive analytics fields. This is by far one of the best conferences. It not only brings leaders on the field together, but also offers practical hands-on with real applications in healthcare, business, manufacturing, government, and financial services.

James McCaffrey- Senior Scientist Engineer, Microsoft

The bottom line: the event was really good — I give it an overall grade of an A- which is (tied for) the best grade I’ve ever given to any conference.

Kenton - Economist, Nike

The emphasis on practical application of analytics to real world business problems and decision making is just right at this conference!

Jason King - Principal Scientist, Procter and Gamble

A 360 degree event - great for anyone who wants to know where data analytics is at and where it's going.

Allison Gonzalez - Decision Science Analyst, USAA

Just do it! Everybody is doing it! I attended PAW San Francisco 2016 and I come back with many new contacts, new friends, and more knowledgeable.

Indu Sriram - Digital Marketing Analytics Manager, Staples

I'm happy we have a conference like Predictive Analytics World - where practitioners like myself can meet other professionals and learn all the latest and greatest. It's a go-to resource and I often attend - hats off to this conference's producers!

Impressions from Machine Learning Week

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Training Workshops – June 2023

Sunday, June 18
Machine Learning with R: A Hands-On Introduction
Jared Lander,
Chief Data Scientist, Leader Analytics

Monday, June 19
The Best of Predictive Analytics: Core Machine Learning and Data Science Techniques
John Elder Ph.D., Founder & Chair, Elder Research

Monday, June 19
Machine Learning Operationalized for Business: Ensuring ML Deployment Delivers Value
James Taylor, CEO, Decision Management Solutions

Monday, June 19
Deep Learning in Practice: A Hands-On Introduction
Bardia Beigi, Applied Scientist II, Microsoft and Prerna Singh, Applied Scientist II, Microsoft

Thursday, June 22
Machine Learning with Python: A Hands-On Introduction
Clinton Brownley, Lead Data Scientist, Tala

Thursday, June 22
The Deadly Dozen: The Top 12 Analytics Mistakes and the Techniques to Defeat Them
John Elder Ph.D., Founder & Chair, Elder Research

Thursday, June 22
Generative AI: From Basic Concepts to Real-World Applications
Martin Musiol, Generative AI Expert,

On-Demand Workshop
Machine Learning Leadership and Practice: End-to-End Mastery
Eric Siegel, Founder, Machine Learning Week

Predictive Analytics World Times

More about Machine Learning Week, Machine Learning and AI

Conference Scope

Whether you call it machine learning, predictive analytics, data science, big data, data mining or artificial intelligence, Machine Learning Week sessions cover the commercial applications of machine learning, across business, finance,

marketing, manufacturing, healthcare, recruitment, government, including the following:

  • Targeting marketing (offline and online)
    • Response modeling
    • Customer retention with churn modeling
    • Acquisition of high-value customers
    • Direct marketing
    • Database marketing
    • Profiling and cloning
  • Online marketing optimization
    • Behavior-based advertising
    • Email targeting
    • Website content optimization
  • Methods Covered
    • decision trees
    • logistic regression
    • neural networks
    • net lift modeling
  • Product recommendation systems
  • Workforce analytics
  • Fraud detection
  • Insurance pricing and selection
  • Credit scoring
  • Other forms of risk management
  • Predictive maintenance
  • Logistics analytics
  • Fault prediction & failure detection
  • Anomaly detection & root cause analysis
  • Supply chain connectivity and optimization
  • Risk management & prevention
  • Smart grid, utilities, and energy operations
  • Credible “AI” approaches with demonstrated value
  • Image & video recognition
  • Internet of Things & smart devices
  • Stream mining & edge analytics
  • Machine learning, ensemble models, & deep learning
  • Process mining & network analyses
  • Mining open & earth observation data
  • Edge analytics & federated learning
  • And more

Predictive Analytics Guide

Predictive analytics is information 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. For more answers on data science visit the Predictive Analytics Guide for reading, training options and other resources.