Stay Up-To-Date on Hot Topics Or Get Left Behind

Sessions are grouped into the five most important contemporary and future “hot topics’ for predictive analytics professionals in business. The five session topics for 2019 are: 
 

Business: Analytics operationalization & management.

Tech: Machine learning methods & advanced topics.

Data: Data strategies & data prep.

Deployment: Predictive model deployment & integration.

Case Studies: Cross industry applications of machine learning. 

Silicon Valley's Hottest Cross-Sector Applications of Deep Learning

A veteran applying deep learning at the likes of Apple, Samsung, Bosch, GE, and Stanford, Mohammad Shokoohi-Yekta kicks off Mega-PAW 2019 by addressing these Big Questions about deep learning and where it's headed:

• Late-breaking developments applying deep learning in retail, financial services, healthcare, IoT, and autonomous and semi-autonomous vehicles

• Why time series data is The New Big Data and how deep learning leverages this booming, fundamental source of data

• What's coming next and whether deep learning is destined to replace traditional machine learning methods and render them outdated

Finding At-Risk Children with Geospatial Machine Learning

In this talk, Dr. Daley will discuss the work of the nonprofit, Predict-Align-Prevent, which implements geospatial machine learning to predict the location of child maltreatment events, strategic planning to optimize the spatial allocation of prevention resources, and longitudinal measurements of population health and safety metrics to determine the effectiveness of prevention programming.  Her goal is to discover the combination of prevention services, supports, and infrastructure that reliably prevents child abuse and neglect.

Finding Analytical Talent – What You Don’t Know About Working with Universities

Dr. Priestley is an academic Associate Dean, who worked for organizations like Accenture and VISA EU, and now manages corporate partnerships with the likes of Blue Cross Blue Shield, Emerson, Equifax, and GE, as well as fire departments and law enforcement. She will discuss the ways that organizations should be thinking about working with universities, but typically don’t – including research, innovation, "externships," training options, recruitment, and other strategic relationships. After this session, you will never look at universities the same way again.

The Disney Story: Competing in Today's Global Analytics Arms Race

We’re in a global analytics arms race, where yesterday’s strategic advantage can quickly become tomorrow’s industry standard.  To stay competitive, companies must continue to invest and evolve at an ever increasing rate.

In this keynote session, Disney Sr. Vice President of Revenue Management and Analytics, Mark Shafer, will discuss his 30-year rags to riches analytical journey, including lessons learned from being on the receiving end of analytics at People Express Airlines to building a science-based analytical team at The Walt Disney Company.

Against All Odds: The Slow, Startling Triumph of Reverend Bayes

The core Bayesian idea, when learning from data, is to inject information — however slight — from outside the data.  In real-world applications, meta-information is clearly needed — such as domain knowledge about the problem being addressed, what to optimize, what variables mean, their valid ranges, etc.  But even when estimating basic features (such as rates of rare events), even vague prior information can be very valuable. This key idea has been re-discovered in many fields, from the James-Stein estimator in mathematics and Ridge or Lasso Regression in machine learning, to Shrinkage in bio-statistics and “Optimal Brain Surgery” in neural networks.  It’s so effective — as I’ll illustrate for a simple technique useful for wide data, such as in text mining — that the Bayesian tribe has grown from being the oppressed minority to where we just may all be Bayesians now.