elastic · gingerwizard · Dec 13, 2019 · Dec 8, 2019 · Dec 9, 2019
diff --git a/Machine Learning/Outlier Detection/Introduction/README.md b/Machine Learning/Outlier Detection/Introduction/README.md
@@ -0,0 +1,6 @@
+# advent-outliers
+
+To run this example, please ensure that you have the following:
+
+* an elasticsearch cluster (version 7.2+) running on `localhost:9200`
+* the dependencies listed in `requirements.txt`. To install these, please run  - `pip install -r requirements.txt`
diff --git a/Machine Learning/Outlier Detection/Introduction/advent-outliers.ipynb b/Machine Learning/Outlier Detection/Introduction/advent-outliers.ipynb
diff --git a/Machine Learning/Outlier Detection/Introduction/requirements.txt b/Machine Learning/Outlier Detection/Introduction/requirements.txt
@@ -0,0 +1,5 @@
+jupyter
+numpy
+requests
+elasticsearch
+sklearn
diff --git a/Machine Learning/Outlier Detection/README.md b/Machine Learning/Outlier Detection/README.md
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+# Outlier Detection
+
+This directory contains examples showcasing Elastic's outlier detection analyses within Machine Learning, which was released in version 7.2.
+
+* [Introduction](Introduction/) shows you how to think about outliers in a 2-dimensional case. We walk you through building up a dataset with particular features and demonstrates how to create and start an outlier detection analysis, and how to analyze the outlier score and feature influence results.