You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
AutoNormalize is a Python library for automated datatable normalization, intended for use with [Featuretools](https://github.com/Featuretools/featuretools). AutoNormalize allows you to build an `EntitySet` from a single denormalized table and generate features for machine learning.
5
+
AutoNormalize is a Python library for automated datatable normalization. It allows you to build an `EntitySet` from a single denormalized table and generate features for machine learning using [Featuretools](https://github.com/Featuretools/featuretools).
*[Machine Learning Demo with Featuretools](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/AutoNormalize%20%2B%20FeatureTools%20Demo.ipynb)
*[Demo with Editing Dependencies](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/Editing%20Dependnecies%20Demo.ipynb)
31
+
*[Kaggle Food Production Dataset Demo](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/Kaggle%20Food%20%20Dataset%20Demo.ipynb)
@@ -84,7 +95,7 @@ Creates a normalized EntitySet from dataframe based on the dependencies given. K
84
95
85
96
<br />
86
97
87
-
####`normalize_entity`
98
+
### `normalize_entity`
88
99
89
100
```shell
90
101
normalize_entity(es, accuracy=0.98)
@@ -101,15 +112,6 @@ Returns a new normalized `EntitySet` from an `EntitySet` with a single entity.
101
112
102
113
<br />
103
114
104
-
### Demos
105
-
106
-
*[Machine Learning Demo with Featuretools](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/AutoNormalize%20%2B%20FeatureTools%20Demo.ipynb)
*[Demo with Editing Dependencies](https://github.com/Featuretools/featuretools/pull/699)
109
-
*[Kaggle Food Production Dataset Demo](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/Kaggle%20Food%20%20Dataset%20Demo.ipynb)
0 commit comments