Difference between revisions of "User:Grberlstein"

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(Day 1 (6/5))
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==='''Day 1 (6/5)'''===
 
==='''Day 1 (6/5)'''===
 
*Refined K-means implementation with the K-means++ seeding described in the [https://datasciencelab.wordpress.com/2014/01/15/improved-seeding-for-clustering-with-k-means/ Data Science Lab] article
 
*Refined K-means implementation with the K-means++ seeding described in the [https://datasciencelab.wordpress.com/2014/01/15/improved-seeding-for-clustering-with-k-means/ Data Science Lab] article
 +
*Started testing the algorithm on random Gaussian distributions, rather than random points
 
*Experimented with visual plotting of the algorithm using Seaborn and Matplotlib
 
*Experimented with visual plotting of the algorithm using Seaborn and Matplotlib
 +
 
==='''Day 2 (6/6)'''===
 
==='''Day 2 (6/6)'''===
 
*Attended RCR training
 
*Attended RCR training
 
*Finished reading the relevant sections of [http://homepages.inf.ed.ac.uk/rbf/BOOKS/JAIN/Clustering_Jain_Dubes.pdf Algorithms for Clustering Data]
 
*Finished reading the relevant sections of [http://homepages.inf.ed.ac.uk/rbf/BOOKS/JAIN/Clustering_Jain_Dubes.pdf Algorithms for Clustering Data]
 
*Experimented with Scikit-learn's implementation of K-means
 
*Experimented with Scikit-learn's implementation of K-means

Revision as of 22:33, 6 June 2017

Griffin Berlstein

Nominally a person.

Readings

Background

Algorithmic Ethics

Clustering and Data Science


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
  • Started testing 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