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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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Interpretable Machine Learning: The Free eBook