diff --git a/program/cohort.ipynb b/program/cohort.ipynb
index 9f69a20..9dcc701 100644
--- a/program/cohort.ipynb
+++ b/program/cohort.ipynb
@@ -42,21 +42,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 236,
+   "execution_count": 2,
    "id": "4b2265b0",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n",
-      "The dotenv extension is already loaded. To reload it, use:\n",
-      "  %reload_ext dotenv\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "#| hide\n",
     "\n",
@@ -100,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 237,
+   "execution_count": 3,
    "id": "32c4d764",
    "metadata": {},
    "outputs": [],
@@ -118,7 +107,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 238,
+   "execution_count": 4,
    "id": "3164a3af",
    "metadata": {},
    "outputs": [],
@@ -141,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 239,
+   "execution_count": 5,
    "id": "7bc40d28",
    "metadata": {},
    "outputs": [],
@@ -160,7 +149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 240,
+   "execution_count": 6,
    "id": "3b3f17e5",
    "metadata": {},
    "outputs": [],
@@ -200,7 +189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 241,
+   "execution_count": 7,
    "id": "942a01b5",
    "metadata": {},
    "outputs": [],
@@ -241,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 242,
+   "execution_count": 8,
    "id": "f1cd2f0e-446d-48a9-a008-b4f1cc593bfc",
    "metadata": {
     "tags": []
@@ -348,7 +337,7 @@
        "4       3450.0  FEMALE  "
       ]
      },
-     "execution_count": 242,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -385,7 +374,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 243,
+   "execution_count": 9,
    "id": "f2107c25-e730-4e22-a1b8-5bda53e61124",
    "metadata": {
     "tags": []
@@ -564,7 +553,7 @@
        "max     6300.000000   NaN  "
       ]
      },
-     "execution_count": 243,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -583,7 +572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 244,
+   "execution_count": 10,
    "id": "1242122a-726e-4c37-a718-dd8e873d1612",
    "metadata": {
     "tags": []
@@ -641,7 +630,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 245,
+   "execution_count": 11,
    "id": "cf1cf582-8831-4f83-bb17-2175afb193e8",
    "metadata": {
     "tags": []
@@ -656,7 +645,7 @@
        "Name: count, dtype: int64"
       ]
      },
-     "execution_count": 245,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -676,7 +665,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 246,
+   "execution_count": 12,
    "id": "cc42cb08-275c-4b05-9d2b-77052da2f336",
    "metadata": {
     "tags": []
@@ -695,7 +684,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 246,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -714,7 +703,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 247,
+   "execution_count": 13,
    "id": "3c57d55d-afd6-467a-a7a8-ff04132770ed",
    "metadata": {
     "tags": []
@@ -733,7 +722,7 @@
        "dtype: int64"
       ]
      },
-     "execution_count": 247,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -756,7 +745,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 248,
+   "execution_count": 14,
    "id": "2852c740",
    "metadata": {},
    "outputs": [
@@ -802,7 +791,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 249,
+   "execution_count": 15,
    "id": "707cc972",
    "metadata": {},
    "outputs": [
@@ -850,7 +839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 250,
+   "execution_count": 16,
    "id": "3daf3ba1-d218-4ad4-b862-af679b91273f",
    "metadata": {
     "tags": []
@@ -930,7 +919,7 @@
        "body_mass_g        640316.716388  "
       ]
      },
-     "execution_count": 250,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -955,7 +944,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 251,
+   "execution_count": 17,
    "id": "1d793e09-2cb9-47ff-a0e6-199a0f4fc1b3",
    "metadata": {
     "tags": []
@@ -1035,7 +1024,7 @@
        "body_mass_g           1.000000  "
       ]
      },
-     "execution_count": 251,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1060,7 +1049,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 252,
+   "execution_count": 18,
    "id": "1258c99d",
    "metadata": {},
    "outputs": [
@@ -1100,7 +1089,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 253,
+   "execution_count": 19,
    "id": "45b0a87f-028d-477f-9b65-199728c0b7ee",
    "metadata": {
     "tags": []
@@ -1154,7 +1143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 254,
+   "execution_count": 20,
    "id": "fb6ba7c0-1bd6-4fe5-8b7f-f6cbdfd3846c",
    "metadata": {
     "tags": []
@@ -1177,21 +1166,16 @@
     "#| code-line-numbers: true\n",
     "\n",
     "import os\n",
-    "import sys\n",
-    "import argparse\n",
-    "import json\n",
     "import tarfile\n",
     "import tempfile\n",
-    "import time\n",
     "import joblib\n",
     "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
-    "from io import StringIO\n",
     "from pathlib import Path\n",
     "from sklearn.compose import ColumnTransformer, make_column_selector\n",
     "from sklearn.impute import SimpleImputer\n",
-    "from sklearn.pipeline import Pipeline, make_pipeline\n",
+    "from sklearn.pipeline import make_pipeline\n",
     "from sklearn.model_selection import train_test_split\n",
     "from sklearn.preprocessing import OneHotEncoder, StandardScaler, OrdinalEncoder\n",
     "\n",
@@ -1350,7 +1334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 255,
+   "execution_count": 21,
    "id": "d1f122a4-acff-4687-91b9-bfef13567d88",
    "metadata": {
     "tags": []
@@ -1360,8 +1344,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\n",
-      "\u001b[32m\u001b[32m\u001b[1m8 passed\u001b[0m\u001b[32m in 0.15s\u001b[0m\u001b[0m\n"
+      "\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\u001b[32m.\u001b[0m\n",
+      "\u001b[32m\u001b[32m\u001b[1m8 passed\u001b[0m\u001b[32m in 0.17s\u001b[0m\u001b[0m\n"
      ]
     }
    ],
@@ -1487,7 +1478,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 256,
+   "execution_count": 344,
    "id": "d88e9ccf",
    "metadata": {},
    "outputs": [],
@@ -1507,7 +1498,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 257,
+   "execution_count": 345,
    "id": "331fe373",
    "metadata": {},
    "outputs": [],
@@ -1534,7 +1525,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 258,
+   "execution_count": 346,
    "id": "3aa4471a",
    "metadata": {},
    "outputs": [
@@ -1581,7 +1572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 259,
+   "execution_count": 347,
    "id": "cdbd9303",
    "metadata": {
     "tags": []
@@ -1662,7 +1653,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 260,
+   "execution_count": 348,
    "id": "e140642a",
    "metadata": {
     "tags": []
@@ -1672,16 +1663,16 @@
      "data": {
       "text/plain": [
        "{'PipelineArn': 'arn:aws:sagemaker:us-east-1:325223348818:pipeline/session1-pipeline',\n",
-       " 'ResponseMetadata': {'RequestId': '26abb4d9-9dc7-44f7-be35-cab1f5a41e02',\n",
+       " 'ResponseMetadata': {'RequestId': '1a583251-fced-460c-ad0f-ddda5589cbed',\n",
        "  'HTTPStatusCode': 200,\n",
-       "  'HTTPHeaders': {'x-amzn-requestid': '26abb4d9-9dc7-44f7-be35-cab1f5a41e02',\n",
+       "  'HTTPHeaders': {'x-amzn-requestid': '1a583251-fced-460c-ad0f-ddda5589cbed',\n",
        "   'content-type': 'application/x-amz-json-1.1',\n",
        "   'content-length': '85',\n",
-       "   'date': 'Tue, 31 Oct 2023 20:24:41 GMT'},\n",
+       "   'date': 'Wed, 01 Nov 2023 17:31:54 GMT'},\n",
        "  'RetryAttempts': 0}}"
       ]
      },
-     "execution_count": 260,
+     "execution_count": 348,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1730,10 +1721,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 261,
+   "execution_count": 349,
    "id": "59d1e634",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "_PipelineExecution(arn='arn:aws:sagemaker:us-east-1:325223348818:pipeline/session1-pipeline/execution/jmk50mirn3i3', sagemaker_session=<sagemaker.workflow.pipeline_context.PipelineSession object at 0x10ec4bfd0>)"
+      ]
+     },
+     "execution_count": 349,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%%script false --no-raise-error\n",
     "#| eval: false\n",
diff --git a/program/setup.qmd b/program/setup.qmd
index bba8279..a7f9c0f 100644
--- a/program/setup.qmd
+++ b/program/setup.qmd
@@ -39,11 +39,11 @@ $ docker ps
 
 ## Configuring AWS
 
-If you don't have one yet, create a new AWS account. You want to use a user with administrative privileges.
+If you don't have one yet, create a new AWS account. A community member noticed that indicating the account is for personal use and his interest is in Machine Learning gave him immediate access to the hardware we need for the program.
 
-We'll need access to `ml.m5.xlarge` instances during the program. By default, the quota for a new account is zero, so you need to request a quota increase. 
-You can do this in your AWS account, under Service Quotas > AWS Services > Amazon SageMaker. Find `ml.m5.xlarge` and request a quota increase for processing 
-jobs, training jobs, transform jobs, and endpoint usage. Ask for a minimum of 3 instances.
+We'll need access to `ml.m5.xlarge` instances. By default, the quota for a new account is zero, but the tip above might fix this problem. If it doesn't, you'll need to request a quota increase. 
+
+You can do this in your AWS account under Service Quotas > AWS Services > Amazon SageMaker. Find `ml.m5.xlarge` and request a quota increase for processing jobs, training jobs, transform jobs, and endpoint usage. Ask for a minimum of 3 instances.
 
 You'll need access to AWS from your local environment. [Install the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) and [configure it](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html) with your 
 `aws_access_key_id` and `aws_secret_access_key.`