Refactor 03-Neptune-ML samples folder (#546)

* Refactor 03-Neptune-ML samples folder

* update changelog

Author: michaelnchin

ChangeLog.md

@@ -3,9 +3,10 @@
 Starting with v1.31.6, this file will contain a record of major features and updates made in each release of graph-notebook.
 
 ## Upcoming
+- Fixed `neptune_ml_utils` imports in `03-Neptune-ML` samples ([Link to PR](https://github.com/aws/graph-notebook/pull/546))
 
 ## Release 4.0.1 (Nov 29, 2023)
-- Fixed @neptune_db_only magics decorator [Link to PR](https://github.com/aws/graph-notebook/pull/543))
+- Fixed @neptune_db_only magics decorator ([Link to PR](https://github.com/aws/graph-notebook/pull/543))
 
 ## Release 4.0.0 (Nov 29, 2023)
 - Added support for Neptune Analytics ([Link to PR](https://github.com/aws/graph-notebook/pull/541))

src/graph_notebook/notebooks/03-Neptune-ML/01-Gremlin/01-Getting-Started-with-Neptune-ML-Gremlin.ipynb

@@ -81,6 +81,20 @@
     "Run the code below to check that your cluster is configured to run Neptune ML."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

src/graph_notebook/notebooks/03-Neptune-ML/01-Gremlin/02-Introduction-to-Node-Classification-Gremlin.ipynb

@@ -74,6 +74,20 @@
    ],
    "metadata": {}
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

src/graph_notebook/notebooks/03-Neptune-ML/01-Gremlin/03-Introduction-to-Node-Regression-Gremlin.ipynb

@@ -73,6 +73,20 @@
     "Run the code below to check that your cluster is configured to run Neptune ML."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

src/graph_notebook/notebooks/03-Neptune-ML/01-Gremlin/04-Introduction-to-Link-Prediction-Gremlin.ipynb

@@ -71,6 +71,20 @@
     "Run the code below to check that this cluster is configured to run Neptune ML."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

src/graph_notebook/notebooks/03-Neptune-ML/01-Gremlin/05-Introduction-to-Edge-Classification-Gremlin.ipynb

@@ -74,6 +74,20 @@
     "Run the code below to check that this cluster is configured to run Neptune ML."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

src/graph_notebook/notebooks/03-Neptune-ML/01-Gremlin/06-Introduction-to-Edge-Regression-Gremlin.ipynb

@@ -72,6 +72,20 @@
     "Run the code below to check that your cluster is configured to run Neptune ML."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,

src/graph_notebook/notebooks/03-Neptune-ML/03-Sample-Applications/02-Job-Recommendation-Text-Encoding.ipynb

@@ -143,6 +143,20 @@
     "First, to check that this cluster is configured to run Neptune ML. Then, (optional) clear existing datasets in the Neptune cluster. And finally, load the Neptune-formartted job recommendatation dataset from `s3://neptuneml-data/kaggle-job-recommend`."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!cp ../neptune_ml_utils.py ."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": null,