Sunday, February 23, 2014

Week 5 : Zipfian Academy - Graphs and Community Detection

The update for last week will be short and quick. Doing these blog posts is getting much harder.

We started the week looking at unsupervised learning techniques like k-means and  hierarchical clustering. We also visited dimension reduction techniques like SVD and NMF. By mid-week, we switched gears to graph analysis  and covered in no particular order BFS, DFS, A*, Dijkstra and community detection in graph networks

Take aways from the week:
  • We had several guest lectures this week. @kanjoya is working on the cutting edge of Natural Language Processing. They help their clients derive actionable intelligence from emotions and intuition. The speaker discussed the general NLP landscape : tools and techniques. I found it interesting that some of their training data comes from The Experience Project
  • @geli gave an interesting talk. They've basically built an OS for energy systems and hope to revolutionize the energy management space 
  • @thomaslevine talk was on open data initiatives around the country. Open Data is one of those things cities like to talk about but very few of them are doing it well
  • Things were switched around this week. We ended the week working on a dataset from one of the partner companies. The dataset recorded mobile ads served to user at various locations, we were supposed to do some exploration and find out the best locations to serve ads to users. The dataset had a couple million records. Trying to wrangle giga-byte sized data on just 4gb of RAM is definitely not fun. I ordered a 16gb RAM kit, should get it by this weekend. If you are thinking of enrolling for the course, you should shoot for at least 8gb of RAM.   

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