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I gave this presentation as part of a series of Python learning sessions at the NCSU Instute for Advanced Analytics and as well as in an analytics consulting interview. For the interview, we were asked to present on a topic in data and analytics of particular interest to us. As a passionate programmer and data scientist, I thought I'd talk about scikit-learn, a machine learning library in Python with a very versatile, extensible API!

These folks were a huge inspiration for me in giving this presentation. Through their articles and videos, I learned a ton about scikit-learn and became a better programmer. I should also note that some of the diagrams in my slideshow came directly from theirs - why reinvent the wheel, right?

Andreas Mueller, Machine Learning with Scikit-learn, PyData NYC 2015

Julie Michelman, Pandas, Pipelines, and Custom Transformers, PyData Seattle 2017

Stephen Hoover, Scaling Scikit-learn, PyData Seattle 2017

Zac Stewart, Using scikit-learn Pipelines and FeatureUnions

Zen Pursuits, Pipelines, FeatureUnions, GridSearchCV, and Custom Transformer