This is the web page for Math 450, taught by Tim Reluga in the spring semester of 2016.
We will learn to model problems and systems using mathematics and computers. We'll be using the python computer language (which I will teach everybody at the start of the course). We'll cover statistical models, cellular automata models, and classical applied-math models. We'll also discuss the nature of modelling, based on readings from Nate Silver's Signal and the Noise.
Office hours will be Mondays, 1:30 - 2:30, or by appointment.
Computer labs: Jan. 20 and 22, 216 Osmond
Due Wednesday, January 20.
Due Friday, January 20.
Due Monday, Feb 1st.
Due Friday, Feb. 5th.
Due Monday, Feb 8th.
Due Wednesday, Feb 17th.
For a formal, structured introduction to computer programming using python, MIT's online course Introduction to Computer Science and Programming is a very helpful reference. Check it out, if you feel like you need more background.
Canopy - python software for scientific computing that we'll make use of in class.
Kaggle public data science site, with competitions.
Command-line murder, a fun way to learn the unix shell (I think?)
Bokeh is a new library for drawing interactive plots in Canopy.
Google's AI win's at Go (sort-of -- only ranks 600th in the world)
A feud is emerging about the CRISPR synthetic biology technology!
Powerball is in the news, which is reporting on excitement over their billion-dollar jackpot. You can find the odds of winning here. Wired has a slightly wrong take-down of the math. But if you want to win, best to be smart about it -- 1, 2, 3, 4, 5. Also, Planet Money's story on the guy who bought all the tickets to win (which is now illegal), just like in the CLASSIC 80's movie Real Genius.
"Big data" is a dominate idea in technological development right now, closely related to our readings of Nate Silver's book. But there is also a lot of pushback right now. Poster-child of model-free big-data inference Google flu trends seemed to work pretty good at first. Now there's another effort-involving critical analysis of this by Olson, Konty, Paladini, Viboud, and Simonsen as well as cheap commentaries by Butler, Lazer, Kennedy, King, and Vespignani, and Tim Harford helping the limitations of data without models.
Stephen Wolfram's enumeration of 1-dimensional spatial rewrite rules.