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Data Science with Social Science data: building predictive models using Python’s Scikit-learn

October 27, 2017 @ 2:00 pm - 4:00 pm

Modern Languages Building (MLB), Room 2001B

We will use Python’s Pandas DataFrames, Matplotlib and Scikit-learn to analyze census data. Participants will use Scikit-learn tools to predict whether income exceeds a particular dollar amount based on the census data. This workshop covers the essential steps to building a predictive model in Python. We will start with an introductory explanation of Anaconda and the Jupyter notebook environment (although not required for the participant, the instructor will be using these tools). We will proceed with topics including: creation and manipulation of Pandas DataFrames and Matplotlib objects and; creation and interpretation of predictive models using Python’s Scikit-learn. Although not required, we recommend that participants have a basic knowledge of Python and Pandas DataFrames.


October 27, 2017
2:00 pm - 4:00 pm
Event Category:


Class size
24 participants, 1 per computer
U-M Affiliated Fee
Marcio Duarte Albasini Mourao