working code

Author: Madhur prashant

0_model_training_pipeline.ipynb

@@ -1422,7 +1422,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

1_batch_transform_pipeline.ipynb

@@ -1239,7 +1239,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

2_realtime_inference.ipynb

@@ -51,6 +51,7 @@
     "import sagemaker\n",
     "import sagemaker.session\n",
     "from datetime import datetime\n",
+    "from utils import load_config\n",
     "from typing import Dict, List\n",
     "from sagemaker.workflow.pipeline_context import PipelineSession"
    ]
@@ -1007,9 +1008,9 @@
   ],
   "instance_type": "ml.t3.medium",
   "kernelspec": {
-   "display_name": "Python 3 (Data Science 3.0)",
+   "display_name": "base",
    "language": "python",
-   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:us-east-1:081325390199:image/sagemaker-data-science-310-v1"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1021,7 +1022,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

config.yml

@@ -9,11 +9,11 @@ aws:
   s3_prefix: mlops-pipeline-model 
 
 presto:
-  host: 3.93.186.209 
-  parameter: "8080"
-  presto_credentials: presto-credentials
-  catalog: tpch
-  schema: tiny
+  host: <0.0.0.0>
+  parameter: "0000"
+  presto_credentials: <presto_credentials>
+  catalog: <catalog>
+  schema: <schema>
 
 ## User needs to configure the following
 pipeline:
@@ -93,7 +93,7 @@ tuning_step:
 
 evaluation_step:
   step_name: Evaluate-Model
-  accuracy_condition_threshold: 0.7
+  accuracy_condition_threshold: 0.40
   instance_type: ml.m5.xlarge
   instance_count: 1
   evaluation_filename: evaluation.json