WKU Reach 2017: Business Data Analytics Poster Competition
RapidMiner has a large presence in the higher education (university) community and we receive some great RapidMiner projects from all around the world. Today I would like to highlight undergraduate business data analytics students at Western Kentucky University's Gordon Ford College of Business. Under the tutelage of Associate Professor Lily Popova Zhuhadar, students presented 14 projects demonstrating how to apply RapidMiner's powerful analytics tools directly into practical business use cases. The 2017 poster session, held on December 1, 2017, was as follows:
Project-1: Predict Which Customers Will Churn! |
- Everett Taylor |
-Andrew Newton |
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Project-2: Predict Which Customers Will Default! Credit Risk Modeling |
- Joe Edwards |
- Andrew Gibbs |
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Project-3: Predict Which Customers |
- Brenden Lutz |
- Aaron Dorris |
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Project-4: Detect Medical Fraud! |
- Dolton Holland |
- Kyle Killebrew |
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Project-5: Predict the Stocks Market Bidding |
- Parker McClean |
- Spencer Embry |
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Project-6: Predict Who Will Click, Buy, Lie, or Die! Web Analytics |
- Abigail Vazquez |
- Cierra Snyder |
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Project-7: Predict iPhone X Buyers! |
- Abdulaziz Aldehaim |
- Faisal Chowdhur |
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Project-8: Predict Credit Card Default! |
- Eric Spiller |
- Kate Mukderink |
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Project-9: Predict Boston |
- Graham Goins |
- Ryan Weddle |
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Project-10: Telecom Segmentations |
- Gus Madsen |
- Kyle Hart |
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Project-11: Churn Propensity |
- Jordan Myers |
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Project-12: Predicting the Best |
- Sarah Smith |
- Jacob Wood |
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Project-13: Phishing or Legit Advertisement? (YouTube Ads) |
- Nicolas Coffell |
- James Roark |
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Project-14: Cross-selling in |
- Nihad Hasanovic |
- Sergio Ortega |
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Congratulations to all WKU students and thank you Dr. Zhuhadar for sharing your amazing work with us!
[All RapidMiner processes and data sets can be downloaded here]