From dc7ab0c75fb3d9fe092b195010aeaa1cc9506c41 Mon Sep 17 00:00:00 2001 From: cfiutak1 Date: Tue, 2 Apr 2019 12:33:14 -0400 Subject: [PATCH] Update Part 1 - Introduction to Machine Learning with scikit-learn.md --- Part 1 - Introduction to Machine Learning with scikit-learn.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Part 1 - Introduction to Machine Learning with scikit-learn.md b/Part 1 - Introduction to Machine Learning with scikit-learn.md index 378a2ad..a2081c4 100644 --- a/Part 1 - Introduction to Machine Learning with scikit-learn.md +++ b/Part 1 - Introduction to Machine Learning with scikit-learn.md @@ -130,7 +130,7 @@ logistic_model.fit(X_train, Y_train) ``` In a very simple case, Logistic Regression can kind of be thought as drawing an -S-shaped line of best fit. Here's an example of where that might come in handy: +S-shaped line of best fit. Here's a visualization: ![Logistic Regression](images/logit.jpeg)