The premier machine learning event –
select a conference:
The premier machine learning event –
select a conference:
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:
Years
Locations
Total Events
Speakers
Sessions
Companies
Attendees
2023 Keynote Speakers
William Wilkins
VP, Chief Risk and Analytics Officer
Gulrez Khan
Data Science Lead
Terry Miller
Executive Director-Predictive Analytics (Global Services)
Vanja Josifovski
CEO & Co-Founder
Sarah Kalicin
Data Scientist
Jen Gennai
Head of Responsible Innovation, Global Affairs
Brandon Southern
Sr. Manager - Business Intelligence
Testimonials
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.
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!
Allison Gonzalez
Decision Science Analyst, USAA
Just do it! Everybody is doing it! I attended PAWSF 2016 and I come back with many new contacts, new friends, and more knowledgeable.
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.
Impressions from Machine Learning Week
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, GenerativeAI.net
On-Demand Workshop
Machine Learning Leadership and Practice: End-to-End Mastery
Eric Siegel, Founder, Machine Learning Week
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.