Revision as of 20:51, 11 June 2017

Griffin Berlstein

Nominally a person.

Readings

Background

Algorithmic Ethics

• Ethics of Algorithms
• Is There an Ethics of Algorithms?
• Toward an Ethics of Algorithms
• Quantifying Search Bias
• Understanding and Designing around Users' Interaction with Hidden Algorithms in Sociotechnical Systems

Clustering and Data Science

• Algorithms for Clustering Data
• K-means Clustering in Python

Project Log For Summer 2017

Week One (5/30 - 6/2)

Day 1 (5/30)

• Attended REU orientation
• Obtained ID card and computer access
• Met with Dr. Guha and discussed broad ideas surrounding the project

Day 2 (5/31)

• Attended Library orientation
• Finished reading Ethics of Algorithms by Thijs Slot. This was the last of the pre-REU reading.
• Started reviewing the basics of Python
• Given crime data sets to review by Dr. Guha

Day 3 (6/1)

• Attended a meeting on proper research practices by Dr. Factor
• Set up direct deposit
• Reviewed the basics of GitHub
• Continued to review Python
• Examined crime data and the various ways it was made publically available

Day 4 (6/2)

• Moved mentor meeting to Wednesday due to scheduling issue
• Started reading background information provided by Dr. Guha
• Set up Jupyter notebook and the various dependent libraries
• Created rough implementation of K-means clustering on random data
• Obtained card access to Dr. Guha's lab
• Posted rough, pre-discussion milestones

Week Two (6/5 - 6/9)

Day 1 (6/5)

• Refined K-means implementation with the K-means++ seeding described in the Data Science Lab article
• Tested the algorithm on random Gaussian distributions, rather than random points
• Experimented with visual plotting of the algorithm using Seaborn and Matplotlib

Day 2 (6/6)

• Attended RCR training
• Finished reading the relevant sections of Algorithms for Clustering Data
• Experimented with Scikit-learn's implementation of K-means

Day 3 (6/7)

• Met with Dr. Guha and discussed the immediate future
• Set the goal to produce an interactive crime map by next Wednesday
• Gathered data from website and began sorting

Day 4 (6/8)

• Created a script to aggregate the data from multiple spreadsheets into a single usable file
• Looked into potential libraries needed to create the interactive map
• Ran into issues with the format of the data location
• Converted the addresses in the data into latitude/longitude coordinates

Day 5 (6/9)

• Found a publically available shape file of the city
• Set up the necessary scripts to display the file
• Ran into an issue with the points not being in the same coordinate system as the shape file

Week Three (6/12 - 6/16)