changes done

Author: madhurprash

0_model_training_pipeline.ipynb

@@ -106,7 +106,7 @@
     "    ParameterString,\n",
     "    ParameterFloat,\n",
     ")\n",
-    "\n",
+    " \n",
     "from sagemaker.estimator import Estimator\n",
     "from sklearn.metrics import roc_auc_score\n",
     "from sagemaker.inputs import TrainingInput\n",

2_realtime_inference.ipynb

@@ -381,7 +381,7 @@
     "\n",
     "## create this from the config param.\n",
     "body_str = \"total_extended_price,avg_discount,total_quantity\\n1,2,3\\n66.77,12,2\"\n",
-    "\n",
+    " \n",
     "response = smr.invoke_endpoint(\n",
     "    EndpointName=endpoint_name,\n",
     "    Body=body_str.encode('utf-8') ,\n",

README.md

@@ -11,7 +11,7 @@ To run this code follow the prerequisites below and then run the notebooks in th
 The following prerequisites need to be in place before running this code.
 
 #### PrestoDB
-
+ 
 We will use the built-in datasets available in PrestoDB for this repo. Following the instructions below to setup PrestoDB on an Amazon EC2 instance in your account. ***If you already have access to a PrestoDB instance then you can skip this section but keep its connection details handy (see the `presto` section in the [`config`](./config.yml) file)***.
 
 1. Create a security group to limit access to Presto. Create a security group called **MyPrestoSG** with two inbound rules to only allow access to Presto.

config.yml

@@ -19,7 +19,7 @@ aws:
       # Boolean that determines whether to encrypt inter-container traffic. 
       # Default value is None.
       encrypt_inter_container_traffic: 
-
+ 
 presto:
   host: <your-presto-server-ip>
   parameter: "<your-presto-port-number"

utils.py

@@ -10,10 +10,10 @@
 logging.basicConfig(format='[%(asctime)s] p%(process)s {%(filename)s:%(lineno)d} %(levelname)s - %(message)s', level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-# utility functions
+#utility functions
 
 make_s3_prefix = lambda x, dttm: f"{x}/yyyy={dttm.year}/mm={dttm.month}/dd={dttm.day}/hh={dttm.hour}/mm={dttm.minute}"
-
+ 
 def print_pipeline_execution_summary(steps, name):
     failed_steps = 0
     steps_that_had_to_retried = 0