anchor.diff:  
   ## Import Sample Data
   
  -For demonstration purpose, a python script is provided to import sample data. It imports 50 sessions of events. In each session, randomly select an user (with user ID "u1" to "u10") to lamd on a page (randomly selected from example.com/page1 to example.com/page20) with referrerId (randomly selected from referrer1.com to referrer10.com) and browser information, the user may view more pages, and may or may not buy an item (with item ID "i1" to "i50").
  +For demonstration purpose, a python script is provided to import sample data. The sample data includes 50 sessions of events. In each session, a randomly selected user (with user ID "u1" to "u10") lands on a page (randomly selected from example.com/page1 to example.com/page20) with referrerId (randomly selected from referrer1.com to referrer10.com) and browser information. The user may view more pages, and may or may not buy an item (with item ID "i1" to "i50").
   
   NOTE: You need to install Python SDK to run the import script. Please follow [Python SDK README](https://github.com/PredictionIO/PredictionIO-Python-SDK) to install.
   
  
positive.code: 
  ## Usage
  
  ### Event Data Requirment
  
  By default, the template requires the following events to be collected:
  
  - page 'view' events with session ID
  - the first page view event can optionally provide the browser and referrer ID
  - user 'buy' event with session ID
  
  The landing page ID, referrer ID, browser information and user's buy event will be used to train the model.
  
  NOTE: You can customize what the "conversion" event is (such as 'subscribe'). It's "buy" item event by default.
  
  #### Input Query:
  
  - landing page ID
  - referrer ID
  - browser
  
  #### Output PredictedResult:
  
  
negative.code: 
  ## Using the Engine
  
  Now, You can retrieve the results. When a user lands on your page "example.com/page9", with referrer "referrer10.com" and browser "Firefox", you can get the predicted lead score by sending this JSON '{ "landingPageId" : "example.com/page9", "referrerId" : "referrer10.com", "browser": "Firefox" }' to the deployed engine. The engine will return a JSON with the score
  
  Simply send a query by making a HTTP request or through the `EngineClient` of an SDK:
  
  