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Emily Gill ecgill

  • University of Colorado
  • Boulder, CO
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ecgill / Pipeline-guide.md
Created February 16, 2018 20:18 — forked from amberjrivera/Pipeline-guide.md
Quick tutorial on Sklearn's Pipeline constructor for machine learning

If You've Never Used Sklearn's Pipeline Constructor...You're Doing It Wrong

How To Use sklearn Pipelines, FeatureUnions, and GridSearchCV With Your Own Transformers

By Emily Gill and Amber Rivera

What's a Pipeline and Why Use One?

The Pipeline constructor from sklearn allows you to chain transformers and estimators together into a sequence that functions as one cohesive unit. For example, if your model involves feature selection, standardization, and then regression, those three steps, each as it's own class, could be encapsulated together via Pipeline.

Benefits: readability, reusability and easier experimentation.
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ecgill / tmux-cheatsheet.markdown
Created February 16, 2018 21:29 — forked from MohamedAlaa/tmux-cheatsheet.markdown
tmux shortcuts & cheatsheet

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname
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ecgill / useful_pandas_snippets.py
Created February 17, 2018 17:47 — forked from bsweger/useful_pandas_snippets.md
Useful Pandas Snippets
# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()
# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])
# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!