Throughout this class, we'll be using several python packages extensively. If you've never used them before, we strongly encourage you to play around with them and get comfortable.
numpy - Python's package that provides high-performance matrix, vector and linear algebra operations
matplotlib - a package for basic plotting and visualization of data
seaborn - a nice visualization package that builds on matplotlib. Produces nicer visualizations, and has some built-in data analytics
All assignments will be turned in using ipython notebooks. If you've never used ipython before, you can either run it in a browser using something like
jupyter, or you can run it interactively from a terminal using:
(One disadvantage of running
ipython –pylab is that it automatically imports numpy and matplotlib. This pollutes the IDE's namespace, and sometimes makes it difficult to port code to non-ipython interpreters, because you won't have the right imports in place…)
I often find it easier to do my code development interactively in the terminal, then save a final notebook to turn in.
If you're more comfortable with IDEs, you may also want to check out