Monday, January 24, 2011

Resolutions

I had written this up after talking to Lin, who asked me about my resolutions, but forgot to publish it. Since it's kind of a tradition for me to list my resolutions on this blog, here they are.

Last year (2010) was an interesting year. I can't really say if it had been good or not, but it was interesting. I didn't consciously keep last year's resolution of "focus on what's important" as close to heart as I should have. It is a very open-ended resolution, so it's pretty difficult to judge how well things went. I also had a tremendous amount of luck: a lot of micro-decisions turned out well, I found the type of work that drives me, I learned a lot, and I made friends in the process.

I had another resolution last year, which was to declare my major. I did. My majors are Pure Math and Applied Math.

For 2011 I have two resolutions lined up. The two are related, and they are even more basic and more open-ended than the ones I had before:

(1) Don't do what I know is wrong.
(2) Do what I think is right.

These two things sound simple, yet those who can abide by them truly inspire me. Actually, of all the people I know, I'm really only certain of one person who does these. I really wish to be able to live up to this person sooner rather than later. (You know who you are.)

The two resolution also sound the same, but they're not. (1) is a subset of (2), and is a much more realistic and less scary target. On the other hand, (2) completes (1); it's what I really should be doing. Hopefully I'll remember both of these for the rest of the year and truly live by them. (So far I'm doing okay. Not perfect, but okay.)

Memorable moments of 2010? Landlord. Buddhist temple. Blogging on Blackberry at Exploratorium on Valentine's day. Conspiracy theories. Grocery trips. Poking ringworms. Being mad at a friend. Forgetting a fellow intern's name in front of >200 people. Failing complex midterm. Logistic Regression. Hiking. TMI. Hiking at TMI. Putnam at Stanford. More hiking. Secret project. Causes. Hotels. Many Hackathons...

End of Entry

Monday, January 10, 2011

Our launch...


I suppose I had a pretty naive view of what a small project launch would feel like.

End of Entry

Friday, December 24, 2010

"What's on your mind?"

Click here to see my post on the Facebook Data Team blog.

Pressing "Publish" on that thing when no one else was around (and with the moral support of other interns) was a great way to end my internship.

Oh and yes, I'm back in Toronto now.

End of Entry

Tuesday, December 21, 2010

Things I learned

Cameron, the Data Science manager at Facebook, dropped an innocuous-sounding question at the intern goodbye dinner last Friday: "What was the most interesting/important thing you learned this term, not necessarily at Facebook?"

I would have responded with something witty, except I'm obviously too slow for that. Thinking back though, enough had happened this term for me to give a non-idiotic answer. In fact, I can list three pretty important things that I learned this term. Here they are, in no particular order:

1) Famous people are famous because they do things. There's nothing more to it, and nothing less.

Being intimidated by people who are famous is something I still haven't gotten over, but between accidentally cutting in front of Zuck in the dish line, asking Donald Knuth a stupid question in his Christmas tree lecture*, and seeing my friend Paul Butler become famous, I realized that their ticket to fame is actually really simple: when they had an idea, they followed through.

Simply put, they did things. They executed.

There really is nothing more to it. I'm sure more of my friends will decide to do things, get noticed, and as a side effect, become famous. There's nothing intimidating or far-fetched about that.

2) I don't know much about statistics.

I was learning statistics in a pretty non-standard (a.k.a. "hands-on") way, which was basically (a) try to solve problems with what I know, (b) fail, (c) read, (d) fail a little bit less. While this had taught me a LOT, the process was the best at teaching me exactly what I don't know. No, I don't mean the cliché and unhelpful "I learned that there's so much more to this subject!" bullshit. The process helped me build a concrete to do list of what subjects to research, what books to read, and what fun projects to attempt. For now though, I'll survive by knowing that logistic regression is the answer to 99% of questions in statistics.

3) When you decide to do things, opportunities come.

Our world is really a land of opportunity. Especially at Facebook, the difference between saying "yes" to something and saying "no" is astronomical. Saying "yes" or just doing interesting things seems like such a simple thing to do, and those who did it (e.g. Paul, Gurrinder, etc.) got great results. I'll be honest though: I haven't been as keen on saying "yes" this term as compared to last term, and it really showed. We worry so much more about macro-decisions like where to go to school and where to do the next internship, so it's funny to notice that micro-decisions such as "should I do this today or next week?" can be just as life-changing.


Well, for better or for worse, that was my term. I did some things I'm proud of and a few that I'm not. I failed a lot, but learned a lot too. Hopefully, in 2011, I won't let trivial fears set me back: I'll do more, try more, and say "yes" more. There's just too much to lose otherwise.

And yes, Facebook was awesome.

End of Entry

*me: "You used n in two different ways!" Knuth: "... to show an equality."

Saturday, October 16, 2010

A better visualization of job posting length vs application

Here's a plot that should have been included in part three of Mining Jobmine. It describes the change in distribution of applications as the length of job posting changes. For each x-value representing a certain length of job posting, the plot gives an estimate on the portion of jobs that has 0 to 22 applications, 23 to 40 applications, 41 to 70 applications and >71 applications. The end points are chosen to be the 25th, 50th and 75th percentiles of the number of applications.

The size of the "0 to 22 applications" category increases steadily as the length of job posting increases from 30-ish to around 500, indicating a drop in application. But as the length of job posting increases beyond 500 words, the size of the bottom-most category decreases. This decrease is offset by an increase in the size of the ">71" category. My guess is that jobs with really long job postings are ones where multiple positions are advertised (e.g. Google job posting...).

Compared to what I had before, this is a much better way of visualizing the correlation between length of job posting and application.

End of Entry