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Update Churn Analysis notebook README description

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Makes the description more consistent with other notebooks.
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Donne Martin 2016-05-05 07:19:00 -04:00
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@ -64,7 +64,7 @@ IPython Notebook(s) used in [kaggle](https://www.kaggle.com/) competitions and b
| Notebook | Description |
|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------|
| [titanic](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/kaggle/titanic.ipynb) | Predict survival on the Titanic. Learn data cleaning, exploratory data analysis, and machine learning. |
| [churn-analysis](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/analyses/churn.ipynb) | Predicts customer churn. Exercises logistic regression, gradient boosting classifers, support vector machines, random forests, and k-nearest-neighbors. Discussion of confusion matrices, ROC plots, feature importances, prediction probabilities, and calibration/descrimination.|
| [churn-analysis](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/analyses/churn.ipynb) | Predict customer churn. Exercise logistic regression, gradient boosting classifers, support vector machines, random forests, and k-nearest-neighbors. Includes discussions of confusion matrices, ROC plots, feature importances, prediction probabilities, and calibration/descrimination.|
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