Packages to install: pip, numpy, pandas, math, matplotlib, pylab, sklearn, ipython
We'll be going through data munging and prediction in pandas and sklearn using kaggle election data. The talk is a workshop to get those with some coding experience (i.e. you can write a loop) thinking about how to use data. More than the code, we'll aim to translate how pandas works as compared to python-before-dataframes; we'll think about how we have to manipulate our data to get it into a machine learning algorithm; and we'll talk about the basic difference between statistics and machine learning.
Level: intermediate programming, beginning data/statistics.
6:45 Doors open, refreshments served. If you run into issues installing a package, please come early to get help before the workshop begins.
7:10pm Metis intro
7:15pm Workshop begins
8:45 - 9pm Mingling
Instructor bio: Katya Vasilaky is a postdoc in applied economics at Columbia University and PyLadies co-organizer. She works on experimental design, causal inference and data related to economic development. She's worked in over a dozen countries and counting! Katya is excited to be an instructor at Girls Who Code this summer.
Thank you to our hospitable host Metis, who has agreed to provide refreshments for the evening! Metis accelerates the careers of data scientists by providing full-time immersive bootcamps, evening professional development courses, online training, and corporate programs. To learn more about their data science training, check out their web site: http://www.thisismetis.com/