October 15, 2019 - 8:00AM
October 16, 2019 - 2:30PM

MIT Campus

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Data fuels machine learning. Without timely, accurate data, machine learning models do not perform well and can give results that are misleading or fail to deliver value. It is vitally important that companies source and prepare data in the right manner - even though the process can require a vast amount of preparatory work and specialist expertise that may appear daunting. Companies should not even consider embarking on a machine learning project before completing this process.

***This MIT CTL Roundtable is exclusively for members of the MIT CTL Supply Chain Exchange and invited guests. If you are not a member of the Exchange and are interested in attending this roundtable as a potential SCE member, please contact ctl-events@mit.edu.

Flyer with dates and locations of rountables

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In this roundtable, participants will explore the challenges of acquiring the right data as well as the work needed to turn data into the fuel that will run machine learning models efficiently. We aim to address these questions among others. 

  • How do you collect the right data?
  • How do you visualize data?
  • How do you prepare the data for analysis?
  • How do you make decisions about the governance and structure of data?

***This MIT CTL Roundtable is exclusively for members of the MIT CTL Supply Chain Exchange and invited guests. If you are not a member of the Exchange and are interested in attending this roundtable as a potential SCE member, please contact ctl-events@mit.edu.

Agenda  |  Map  |  FAQ

Agenda:

Tuesday, October 15
   8:30 Registration Check-In
   9:00 Welcome and Introductions
   9:30 Session I: Importance of Data
 10:30 Break
 11:00 Session II: Future State Data Governance Structures and Policies
 12:00 Lunch
   1:00 Session III: Managing Transformation and Change through Use-Case-Based Prioritization
   2:00 Break
   2:30  Session IV: Collecting the Right Data
   3:00 Break
   4:00 Closing: Key Take-Aways Day 1
   5:00 Informal Reception at Champions Restaurant, Cambridge Marriott
Wednesday, October 16
   8:30 Recap of Day 1
   9:00 Session V: Understanding Your Data & Data Wrangling
 10:30 Break
 11:00 Session VI: Data Visualization
 12:00 Lunch
   1:00 Computational and Visual Education (CAVE) Lab Session
   1:30 Closing: Key Take-Aways from Day 2
   2:30 Adjourn

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