1. After the Poster Session

2. Assignment 11 Problem Shift “The Fresh Mind”

3. Assignment 11 Your goal is to take someone else’s data set from the class And improve their model any way you can – Could be new features (preferred option!) – Could be a different statistical/data mining framework

4. Assignment 11 Write a report that discusses your process You don’t need to prepare a presentation But be ready to discuss your work in class

5. Assignment 11 You will be graded both on – Your work on the new data set – Whether you obstructed someone from working on your data set You won’t be graded on whether they do a good job with your data But you will be graded down if they don’t get your data until Saturday night, or if you don’t give it to them in a usable form, or if you don’t explain what “RYAN7” means

6. Assignment 10 You will be graded both on – Your work on the new data set – Whether you obstructed someone from working on your data set You won’t be graded on whether they do a good job with your data But you will be graded down if they don’t get your data until Saturday night, or if you don’t give it to them in a usable form, or if you don’t explain what “SAM3” means

7. Readings for next class Fischer, G. (2004) Social Creativity: Turning Barriers into Opportunities for Collaborative Design. Proceedings of the Participatory Design Conference (PDC’04), 152-161. Veeramachaneni, K., O’Reilly, U., Taylor, C. (2014) Towards feature engineering at scale for data from massive open online courses. arXiv preprint 1407.5238.

8. Upcoming classes 4/29 Collaboration in Feature Engineering 5/4 Special Session: Python 5/6 Sustained Iteration