Update README.md

README.md

@@ -33,16 +33,13 @@ pipeline_tag: "structured-data-classification"
 
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-# Classification with TensorFlow Decision Forests 
-#### Using TensorFlow Decision Forests for structured data classification
-
+#TensorFlow Decision Forests for structured data classification
  <br />
-##### This example uses Gradient Boosted Trees model in binary classification of structured data, and covers the following scenarios:
-
-1. Build a decision forests model by specifying the input feature usage.
-2. Implement a custom Binary Target encoder as a Keras Preprocessing layer to encode the categorical features with respect to their target value co-occurrences, and then use the encoded features to build a decision forests model.
-
-The example uses Tensorflow 7.0 or higher. It uses the US Census Income Dataset containing approximately 300k instances with 41 numerical and categorical variables. This is a binary classification problem to determine whether a person makes over 50k a year. 
-
-Author: Khalid Salama  <br /> 
-Adapted implementation: Tannia Dubon
+#### Use TF's Gradient Boosted Trees model in binary classification of structured data
+* Build a decision forests model by specifying the input feature usage.
+* Implement a custom Binary Target encoder as a Keras Preprocessing layer to encode the categorical features with respect to their target value co-occurrences, and then use the encoded features to build a decision forests model.
+<br />
+###The example uses Tensorflow 7.0 or higher. It uses the US Census Income Dataset containing approximately 300k instances with 41 numerical and categorical variables. This is a binary classification problem to determine whether a person makes over 50k a year. 
+<br />
+###Author: Khalid Salama   
+###Adapted implementation: Tannia Dubon