Updated notebook folders

getting-started/train-within-notebook/score.py

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+import pickle
+import json
+import numpy as np
+from sklearn.externals import joblib
+from sklearn.linear_model import Ridge
+from azureml.core.model import Model
+
+
+def init():
+    global model
+    # note here "best_model" is the name of the model registered under the workspace
+    # this call should return the path to the model.pkl file on the local disk.
+    model_path = Model.get_model_path(model_name='best_model')
+    # deserialize the model file back into a sklearn model
+    model = joblib.load(model_path)
+
+
+# note you can pass in multiple rows for scoring
+def run(raw_data):
+    try:
+        data = json.loads(raw_data)['data']
+        data = np.array(data)
+        result = model.predict(data)
+
+        # you can return any data type as long as it is JSON-serializable
+        return result.tolist()
+    except Exception as e:
+        result = str(e)
+        return result