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Beverly Wright, Executive Director, Business Analytics Center, Georgia Institute of Technology at MLconf ATL 2016


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Solving for Why: Impact of Machine Learning for Business Decision-Making: Our abilities to create and harness volumes of data seem to have brought expectations for the development and application of more advanced modeling to support various levels of decision-making. The business problems and opportunities we can and strive to solve are well positioned to increase in number, breadth, and complexity.

As many organizations forge into uncomfortable and foreign territory to build more advanced analytics capabilities, the need for an academic partner tends to become increasingly apparent, and forming meaningful and active partnerships with academic institutions provide a number of benefits for the business community, rising talent, faculty, and other constituents.

Published in: Technology
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Beverly Wright, Executive Director, Business Analytics Center, Georgia Institute of Technology at MLconf ATL 2016

  1. 1. Solving for Why: Impact of Machine Learning on Business Decision-Making Beverly Wright, PhD, CAP Executive Director Business Analytics Center
  2. 2. Overview 2 Application of Machine Learning for Business Questions Closing Remarks Defined: Machine Learning Reasoning: hypothesis vs data initiation points D R A C
  3. 3. Vision The Vision of the Business Analytics Center, Georgia Tech: To be a nationally recognized Center in business analytics, sought-after partner for business analytics opportunities and challenges, renowned for our emphasis on experiential learning and innovative research. 3
  4. 4. 4Definition: machine learning “constructing algorithms that can analyze and learn from data in order to categorize such data and make related predictions. “…it’s about enabling computers to learn things they have not necessarily been programmed to learn.” D R A C
  5. 5. 5Hypothesis vs Data Driven Analytics Initiation Business question / Hypothesis / Data / Testing / Confirm / Deny / Conclusion / Action
  6. 6. 6Hypothesis vs Data Driven Analytics Initiation Data / Patterns / Optimal Method / Conclusion / Action
  7. 7. 7Efficiencies we can gain… Data initiated approach • Supervised • Unsupervised D R A C
  8. 8. 8Illustration: flip flop wearing Process – • Identify important variables • Grouping variables – keep and redundancy • Relationships • Transformations • Techniques
  9. 9. @GeorgiaTechBsch 9/23/2016 Examples from Business
  10. 10. 10Reservation Cancellations Meaning of cancellation Factors to consider • Traveler • Purpose • Weather • Location Possible analytics methods D R A C
  11. 11. 11Home Auctions Number of bids, views, page hits, sale Location Home quality Inventory Buyer Macroeconomics D R A C
  12. 12. 12Influencing / Encouraging Altruistic Behavior Behaviors • Types of altruism • Frequency • Intensity Volunteer & Organization: Identification Attributes Interactions and communications D R A C
  13. 13. @GeorgiaTechBsch 9/23/2016 The Future for Machine Learning
  14. 14. 14 D R A C
  15. 15. 15 “We don’t all have to become data scientists in order to work with the machine. The machine needs to become more human and work with us” KRIS HAMMOND CHIEF SCIENTIST, NARRATIVE SCIENCE D R A C
  16. 16. 16 D R A C Some people don't like change, but you need to embrace change if the alternative is disaster. ~ Elon Musk
  17. 17. @GeorgiaTechBsch 9/23/2016 Business Analytics Center Learn More
  18. 18. Upcoming Event: Business Analytics Think Tank Roundtable – Use and Impact of Artificial Intelligence in Analytics 18 D R A C
  19. 19. Executive Education 19 D R A C
  20. 20. 20 D R A C
  21. 21. Thanks Business Analytics Center Beverly Wright, PhD, CAP Executive Director