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 Learn how to build a complex machine learning pipeline without writing a single line of code using the designer.
 
-This pipeline trains 2 **two-class boosted decision tree** classifiers to predict common tasks for customer relationship management (CRM) systems - customer churn. The data values and labels are split across multiple data sources and scrambled to anonymize customer information, however, we can still use the designer to combine data sets and train a model using the obscured values.
+Open the **Binary Classification - Customer Relationship Prediction** sample pipeline in the designer homepage. This pipeline trains 2 **two-class boosted decision tree** classifiers to predict common tasks for customer relationship management (CRM) systems - customer churn. The data values and labels are split across multiple data sources and scrambled to anonymize customer information, however, we can still use the designer to combine data sets and train a model using the obscured values.
 
 Because you're trying to answer the question "Which one?" this is called a classification problem, but you can apply the same logic shown in this sample to tackle any type of machine learning problem whether it be regression, classification, clustering, and so on.