Linklog - Week 9

• I found a interesting company called Data Made, from Chicago. A civic technology company working in projects related to open data.
• They are also the creators of Dedupe, a Python project to perform data deduplication. It uses a similar approach to the one we use for hotel deduplication @TrustYou.

Some articles both old and new:

• Github is not your CV
• The hidden story behind the code that runs our lives
• Does balancing classes improves classifier performance
• Data science competitions to save the world

Recently two interesting articles about software developers in Colombia were written:

• "Not a single Colombian university teaches software engineering. Really. Not even one."
• Colombian startups don’t have an engineering deficit. Really, they don’t.

The first one is from Alexander Torrenegra and the other was written by Juan Pablo Buritica. Juan Pablo somehow rebuts Alexander some of Alexander's claims. I think Both make interesting points and I think they have the experience and the authority to talk about the subject. I share a bit more the opinion of Alexander as I think Computer Science education in Colombia is not good and need an overhaul. I would love to write a small piece on my experience as I graduated from a top Colombian university and I believe the education on computer science related topics is precarious.

Thanks to the Mining Masive Data Sets class on Coursera and that I started getting curious curious about it. I wanted to explore a bit more and I downloaded the my friends dataset from Facebook and imported into Gephi, a tool for Graph visualization and analysis.

Gephi interface.

Below a couple of interesting links for people that want to do the same:

https://storify.com/ I found this tool to be really nice to keep a log of event and add social network based stories.

http://www.chokkan.org/software/simstring/ I have been taken the MDDS class on Coursera. Challenging but super interesting. I wanted to use LSH to do a sort of hashing of near duplicate short sentences. It is a small dataset so I believe this algorithm will work actually better.

http://ergoemacs.org/emacs/elisp_compact_empty_lines.html Awesome snippet, specially for Python development on Emacs