Last week I was in São Paulo, Brazil to visit Insper, a small private college in the process of starting a new engineering program. The first semester of the program, with the first group of 90 students, is wrapping up this week.
The engineering faculty at Insper have been working with Olin for several years. Their curriculum is similar to Olin’s in some ways, but of course they have designed it for their students and environment. One awesome thing: all students learn Python in the first semester, as I discovered when I visited their library:
And they all take a version of Modeling and Simulation, a class I helped develop at Olin, along with John Geddes and Mark Somerville. They have an excellent FabLab, which was hopping during the last week of classes:
Visting São Paulo was exciting for me — it was my first time in Brazil, and my first time in South America. I used Duolingo to learn some Portuguese, which turned out to be more useful than I expected. I didn’t get much past “Bom dia” and “Obrigado”, but I found that since I know some Latin, Spanish, and French, I could read a lot of Portuguese, especially more technical material, which uses a lot of cognates. I might even have created a new word: talking about Rube Goldberg contraptions, I suggested “contrapção”. That’s a word now.
The Insper faculty are working hard and creating an amazing new program. And the students are great. I sat in on their intro Python class and had a chance to work with a few student teams. They came up with some great projects, some of them very ambitious for an intro class, including one team using OpenCV for facial recognition.
But I am happy to be home, at least for a couple of weeks. Next trip: Austin TX for SciPy!
In the last few weeks I’ve been to the Netherlands and Chicago, and tomorrow I am off to Brazil. But I spent most of this week in my office, enjoying the luxury of working on just one thing: a paper about survival analysis and marriage patterns in the U.S. I just submitted it for review, so watch this space for more.
Here’s a picture of me outside my office, featuring covers from translations of my books:
Also this week I got a pleasant surprise in the mail, a signed copy of a new book by an old friend, Dror Feitelson: Workload Characterization for Computer Systems Performance Evaluation. Here it is in its new home:
My SciPy strategy has gone horribly wrong. I submitted two talks and a tutorial with the expectation that 1.0 of my proposals would be accepted, on average. But the vagaries of the binomial distribution bit me: all three were accepted. So I am scrambling to get ready.
My tutorial on statistical inference is ready to go. As it turns out, Chris Fonnesbeck proposed a similar tutorial at a more advanced level, so we re-titled our tutorials as Computational Statistics I and Computational Statistics II. We are scheduled back to back, and each of us is planning to help out during the other’s session. Both tutorials are now full!
One of my talks is in the Computational Social Science thread, where I will present “Will Millennials Ever Get Married?” I’ll present results from applying survival analysis to data from the National Survey of Family Growth (NSFG). A basic version of the analysis appears in Chapter 13 of Think Stats, 2nd edition. What I am working on now is a more careful analysis using data from earlier and later cycles of the NSFG.
I am close to finishing off the results I want to present. Here’s a screenshot of the current status:
My second talk is on Digital Signal Processing in Python. This is the only talk I have not presented before, but it is based on Think DSP and the class I taught in the spring. I have tons of material; the hard part will be selecting elements that make a complete and coherent talk.
This week I am one of several Olin professors helping out with the Olin Collaboratory Summer Institute. This year we have 55 participants, including faculty from universities around the country (like Oklahoma and Vermont) and the world (like Saudia Arabia, India, and Australia).
During the first half of the week, we lead workshops where participants learn tools for curriculum design. On Monday Mark Somerville and I lead a workshop on understanding students and designing courses and programs that serve their needs. Here’s a picture of me saying something apparently important:
This weekend I was at the Open Data Science Conference, here in Boston, for a book signing (with thanks to the nice people at O’Reilly Media) and to present “Learning to Love Bayesian Statistics”. Here’s an audience shot of the presentation (with thanks to @kjchoi101):
My slides are at http://tinyurl.com/lovebayes. Video should be available soon — I just hope they edit the 5-10 minutes I spent getting wireless to work. Next time someone suggests I should download my slides ahead of time, I will listen!
Comments Off on Learning to Love Bayesian Statistics at ODSC
Yesterday I was in Chicago for a full-day workshop on Bayesian statistics at Orbitz Worldwide. In the morning I presented “Learning to Love Bayesian Statistics”, an overview of Bayesian approaches and my attempt to debunk the myths. The attendees seemed interested, and asked great questions. Their photographer was kind enough to share some photos from the event; here’s a shot from the discussion that broke out after the talk:
Later I presented a customized version of my workshop, “Bayesian Statistics Made Simple.” Again, it was a great group of people with lots of excellent and challenging questions. As always, it’s interesting for me to hear about the problems people are working on and to apply data science tools to new challenges.
I was only in Chicago for 36 hours, but I got to walk around quite a bit, and enjoyed the city (and the perfect weather!).
This week I am visiting the University College at Twente, which is in the process of creating a new program in Technology and Liberal Arts & Sciences (ATLAS). When I arrived yesterday, they were just putting the new sign on the building:
Today I am teaching two workshops, one based on the Joy and Beauty of Computing curriculum, and one on Python.
Will Millennials Ever Get Married? Survival Analysis and Marriage Data
Recent studies report that an increasing share of Americans have never married, which suggests that current young adults might marry at lower rates than previous generations. Using data from a national survey, we find that successive generations are getting married later, but our predictions suggest that the fraction of people who eventually marry will not change substantially. Our analysis uses Pandas for data extraction and cleaning, bootstrap methods for working with stratified surveys, lifelines for survival analysis, and time series analysis with statsmodels. All code and data for this study is in a public repository.
Basic Sound Processing in Python
Digital signal processing (DSP) has applications in all areas of engineering and science, but DSP methods are not widely known. Python provides an opportunity to make DSP more accessible. In this talk, I present an introduction to DSP focused on sound-processing applications. I present tool for working with digital signals using NumPy, SciPy and IPython. Examples include spectral analysis of music, spectrograms, noise, filtering, and system characterization. This material is based on Think DSP, a work-in-progress book available at think-dsp.com.
It looks like there will be a lot of other great talks. I am looking forward to the conference in July!
One of the joys of working on free books is the chance to collaborate with people all over the world. The Python version of How to Think Like a Computer Scientist was translated by Jeff Elkner in 2000 (plus or minus), but I never met him in person until PyCon 2013!
This year, I finally met Charles “Dr. Chuck” Severance, who wrote Python for Informatics, which started as a modified version of How to Think, but has transmogrified into a substantially different new book, which Chuck uses in his Coursera online classes.