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.

They are:

* ''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:

''ipython --pylab''

(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 ''spyder'' or ''pycharm''.