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Four Deep Track Themes at Predictive Analytics World, Oct in New York


 
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Predictive Analytics World for Business New York’s (Oct. 29-Nov. 2) rich program of brand name case studies and industry leaders covers deployed machine learning — across these topics: business, tech, marketing, and case studies.



Predictive Analytics World for Business - Don't Miss These Four Deep Track Themes
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Predictive Analytics - Get Up to Speed on These Topics

Predictive Analytics World for Business New York’s (Oct. 29-Nov. 2) rich program of brand name case studies and industry leaders covers deployed machine learning — across these topics:



Track 1: BUSINESS
Analytics strategy & operationalization – Project management, project leadership, and organizational process — example sessions:

  • Addressing a Public Health Crisis in the NYC Mayor's Office
  • Just-In-Time Skills Training at LinkedIn
  • Data Science Driven Insights at The Clorox Company
  • Value Creation Through Analytics Innovation at Prudential Financial
  • Accelerating Data Science Innovation at Comcast
  • Operationalizing Analytics at Honeywell
  • Winning the Right Marketplace Talent with Analytics at Intel
  • Project Management for Data Scientists at Citigroup
  • Operationalizing Analytics at John Hancock

Track 2: TECH
Predictive modeling methods – Core analytical and machine learning techniques, in-depth — example sessions:
  • Getting the Best Out of Hand-Tagged Training Data at Bloomberg
  • Time Series Crime Prediction with Twitter in New York City
  • Random Forests and Gradient Boosting Machines at Citigroup
  • Demand Forecasting with Machine Learning at Micron Technology
  • Machine Learning vs. Feature Engineering
  • Three Steps for Improving Data Quality for Predictive Analytics
  • Ask the Experts about Best Practices
  • Understanding Complex Predictive Models
  • Solving for the Conflict Between Laws and Analytics


Track 3 (Day 1): MARKETING
Marketing & market research analytics – Machine learning applications such as targeting customer acquisition, optimizing retention, and uplift modeling — example sessions:

  • Retention Modeling in Uncertain Economic Times at Paychex
  • Predicting Customer Preferences at Walmart
  • Predicting Brand Love with Wireless Behaviors at Verizon Wireless
  • Acquisition Funnel for Higher Education at Becker College
  • Real-Time Automation to Build Relationships & Retain Customers
  • Which Predictive Model Will Best Help Increase Retention?
  • Using Rapid Experiments and Uplift Modeling to Optimize Outreach at Scale


Track 3 (Day 2): CASE STUDIES
Varied business applications – Examples from the front lines where deployed machine learning taps into the most powerful value propositions, across business functions — example sessions:

  • What Makes TV Content Work at BBC Worldwide?
  • Implementing a Risk Model in the Maritime Industry at RightShip
  • The Limits of Surveys and the Power of Google Search Data
  • Customer Journey Analytics: Blazing Paths to Customer Success
  • Advancing Hydroponics through IoT Analytics
  • Leveraging Machine Learning for Realtime Pricing in Truck Logistics

Do Not Miss This Groundbreaking Conference



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