updating readmes

microsoftml/101/README.md

@@ -2,16 +2,16 @@
 
 This section introduces short examples on simple tasks. The following samples are available:
 
-Sample|Code|
+Sample|Description|Code|
 |-|-|
+|Use a **regression** to predict wine quality with RevoscalePy|[Code](plot_regression_wines_revoscale.py)|
+|Use a **regression** to predict wine quality with *microsoftml*|[Code](plot_regression_wines.py)|
+|Doing **feature selection** using mutual information|[Code](plot_mutualinformation.py)|
 |Implementing **binary classification**|[Code](plot_binary_classification.py)|
+|Implementing **multi-class classification**|[Code](plot_iris.py)|
 |Working with **categorical features**|[Code](plot_categorical_features.py)|
 |Using formulas|[Code](plot_formula.py)|
-|Classifying images using image featurization|[Code](plot_image_featurizer_classify.py)|
-|Finding similar images using image featurization|[Code](plot_image_featurizer_match.py)|
-|Implementing **multi-class classification**|[Code](plot_iris.py)|
 |Using a **loss function**|[Code](plot_loss_function.py)|
 |Working with input schemas|[Code](plot_mistakes.py)|
-|Doing **feature selection** using mutual information|[Code](plot_mutualinformation.py)|
-|Use a **regression** to predict wine quality with *RevoscalePy*|[Code](plot_regression_wines_revoscale.py)|
-|Use a **regression** to predict wine quality with *microsoftml*|[Code](plot_regression_wines.py)|
+|Classifying images using image featurization|[Code](plot_image_featurizer_classify.py)|
+|Finding similar images using image featurization|[Code](plot_image_featurizer_match.py)|

microsoftml/README.md

@@ -5,17 +5,17 @@ The following samples are available
 
 |Category|Sample|Code|
 |-|-|-|
-|Basic|Implementing **Binary Classification**|[Code](101/plot_binary_classification.py)|
-|Basic|Working with **Categorical Features**|[Code](101/plot_categorical_features.py)|
-|Basic|Using formulas|[Code](101/plot_formula.py)|
-|Basic|Classifying images using image featurization|[Code](101/plot_image_featurizer_classify.py)|
-|Basic|Finding similar images using image featurization|[Code](101/plot_image_featurizer_match.py)|
-|Basic|Implementing **Multi-class Classification**|[Code](101/plot_iris.py)|
-|Basic|Using a **Loss function**|[Code](101/plot_loss_function.py)|
-|Basic|Working with input schemas|[Code](101/plot_mistakes.py)|
-|Basic|Doing **feature selection** using mutual information|[Code](101/plot_mutualinformation.py)|
-|Basic|Use a **regression** to predict wine quality with *RevoscalePy*|[Code](101/plot_regression_wines_revoscale.py)|
-|Basic|Use a **regression** to predict wine quality with *microsoftml*|[Code](101/plot_regression_wines.py)|
+|Basic|Use a **regression** to predict wine quality with RevoscalePy|[Code](plot_regression_wines_revoscale.py)|
+|Basic|Use a **regression** to predict wine quality with *microsoftml*|[Code](plot_regression_wines.py)|
+|Basic|Doing **feature selection** using mutual information|[Code](plot_mutualinformation.py)|
+|Basic|Implementing **binary classification**|[Code](plot_binary_classification.py)|
+|Basic|Implementing **multi-class classification**|[Code](plot_iris.py)|
+|Basic|Working with **categorical features**|[Code](plot_categorical_features.py)|
+|Basic|Using formulas|[Code](plot_formula.py)|
+|Basic|Using a **loss function**|[Code](plot_loss_function.py)|
+|Basic|Working with input schemas|[Code](plot_mistakes.py)|
+|Basic|Classifying images using image featurization|[Code](plot_image_featurizer_classify.py)|
+|Basic|Finding similar images using image featurization|[Code](plot_image_featurizer_match.py)|
 |Advanced|Tuning model **hyperparameters** using a grid search|[Code](202/plot_grid_search.py)|
 |Advanced|Implementing **sentiment analysis**|[Code](202/plot_sentiment_analysis.py)|
 |Advanced|Implementing **text featurization**|[Code](202/plot_text_featurization.py)|