diff --git a/01_exploratory_data_analysis.ipynb b/01_exploratory_data_analysis.ipynb
index f5a7964..ebd7db3 100644
--- a/01_exploratory_data_analysis.ipynb
+++ b/01_exploratory_data_analysis.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "cellView": "form",
     "id": "ur8xi4C7S06n",
@@ -130,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -172,28 +172,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "BUCKET_NAME          = \"gcp-data-science-demo-fraudfinder\"\n",
-      "PROJECT              = \"gcp-data-science-demo\"\n",
-      "REGION               = \"us-central1\"\n",
-      "ID                   = \"22jof\"\n",
-      "FEATURESTORE_ID      = \"fraudfinder_22jof\"\n",
-      "MODEL_NAME           = \"ff_model\"\n",
-      "ENDPOINT_NAME        = \"ff_model_endpoint\"\n",
-      "TRAINING_DS_SIZE     = \"1000\"\n",
-      "\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "PROJECT_ID = GCP_PROJECTS[0]\n",
     "BUCKET_NAME = f\"{PROJECT_ID}-fraudfinder\"\n",
@@ -213,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "id": "0c4746a0c78c",
     "tags": []
@@ -247,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "id": "079accfc15e2",
     "tags": []
@@ -305,79 +288,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "id": "f0405eb973fb",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Finished job_id: b19dfee7-693c-4a0b-9ad1-f14dbed3846b\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>NUM_TX</th>\n",
-       "      <th>MIN_TX_DATE</th>\n",
-       "      <th>MAX_TX_DATE</th>\n",
-       "      <th>NUM_CUSTOMERS</th>\n",
-       "      <th>NUM_TERMINALS</th>\n",
-       "      <th>MIN_TX_AMOUNT</th>\n",
-       "      <th>AVG_TX_AMOUNT</th>\n",
-       "      <th>MAX_TX_AMOUNT</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>148017332</td>\n",
-       "      <td>2022-01-01 00:00:00+00:00</td>\n",
-       "      <td>2025-12-31 23:59:59+00:00</td>\n",
-       "      <td>49993</td>\n",
-       "      <td>5000</td>\n",
-       "      <td>0E-9</td>\n",
-       "      <td>55.005808727</td>\n",
-       "      <td>1110.460000000</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      NUM_TX               MIN_TX_DATE               MAX_TX_DATE  \\\n",
-       "0  148017332 2022-01-01 00:00:00+00:00 2025-12-31 23:59:59+00:00   \n",
-       "\n",
-       "   NUM_CUSTOMERS  NUM_TERMINALS MIN_TX_AMOUNT AVG_TX_AMOUNT   MAX_TX_AMOUNT  \n",
-       "0          49993           5000          0E-9  55.005808727  1110.460000000  "
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "run_bq_query(\n",
     "    \"\"\"\n",
@@ -423,76 +339,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "id": "daf0467aaeb5",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Finished job_id: 3ec35098-3dbb-4553-967a-fdea8baadb3c\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>TX_FRAUD</th>\n",
-       "      <th>NUM_TX</th>\n",
-       "      <th>OVR_TOTAL_TX</th>\n",
-       "      <th>PCT_TOTAL_TX</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0</td>\n",
-       "      <td>145062042</td>\n",
-       "      <td>148017332</td>\n",
-       "      <td>0.980034</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>2955290</td>\n",
-       "      <td>148017332</td>\n",
-       "      <td>0.019966</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   TX_FRAUD     NUM_TX  OVR_TOTAL_TX  PCT_TOTAL_TX\n",
-       "0         0  145062042     148017332      0.980034\n",
-       "1         1    2955290     148017332      0.019966"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "run_bq_query(\n",
     "    \"\"\"\n",
@@ -543,127 +395,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "id": "c41e0815b2b3",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Finished job_id: be2f3aff-3b4f-48e8-96d1-39dd24ad4cd2\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>ROUNDED_TX_AMOUNT</th>\n",
-       "      <th>NUM_TX</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0E-9</td>\n",
-       "      <td>25292</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1.000000000</td>\n",
-       "      <td>98178</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>2.000000000</td>\n",
-       "      <td>208129</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3.000000000</td>\n",
-       "      <td>381410</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>4.000000000</td>\n",
-       "      <td>616521</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>927</th>\n",
-       "      <td>1008.000000000</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>928</th>\n",
-       "      <td>1033.000000000</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>929</th>\n",
-       "      <td>1051.000000000</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>930</th>\n",
-       "      <td>1102.000000000</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>931</th>\n",
-       "      <td>1110.000000000</td>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>932 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    ROUNDED_TX_AMOUNT  NUM_TX\n",
-       "0                0E-9   25292\n",
-       "1         1.000000000   98178\n",
-       "2         2.000000000  208129\n",
-       "3         3.000000000  381410\n",
-       "4         4.000000000  616521\n",
-       "..                ...     ...\n",
-       "927    1008.000000000       1\n",
-       "928    1033.000000000       1\n",
-       "929    1051.000000000       1\n",
-       "930    1102.000000000       1\n",
-       "931    1110.000000000       1\n",
-       "\n",
-       "[932 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "transaction_amount_dist = run_bq_query(\n",
     "    \"\"\"\n",
@@ -697,29 +434,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {
     "id": "54039166d146",
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<iframe\n",
-       "    scrolling=\"no\"\n",
-       "    width=\"100%\"\n",
-       "    height=\"545px\"\n",
-       "    src=\"iframe_figures/figure_24.html\"\n",
-       "    frameborder=\"0\"\n",
-       "    allowfullscreen\n",
-       "></iframe>\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Create histogram of transaction amounts\n",
     "transaction_amount_interactive_histogram = px.bar(\n",
@@ -767,100 +487,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {
     "id": "e3ae4a0f60f6",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Finished job_id: 214b23b5-1550-4505-9430-671c29ca7173\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>CUSTOMER_ID</th>\n",
-       "      <th>NUM_TX</th>\n",
-       "      <th>AVG_TX_AMOUNT</th>\n",
-       "      <th>PCT_TX_FRAUD</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>7228491864464655</td>\n",
-       "      <td>5425</td>\n",
-       "      <td>52.659249770</td>\n",
-       "      <td>0.009401</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>5406457556416978</td>\n",
-       "      <td>4584</td>\n",
-       "      <td>33.198776178</td>\n",
-       "      <td>0.000218</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0683522698674547</td>\n",
-       "      <td>3314</td>\n",
-       "      <td>99.278455039</td>\n",
-       "      <td>0.000302</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1020433424310577</td>\n",
-       "      <td>4290</td>\n",
-       "      <td>83.534331002</td>\n",
-       "      <td>0.000233</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>8314565180058922</td>\n",
-       "      <td>5841</td>\n",
-       "      <td>20.741090567</td>\n",
-       "      <td>0.000171</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        CUSTOMER_ID  NUM_TX AVG_TX_AMOUNT  PCT_TX_FRAUD\n",
-       "0  7228491864464655    5425  52.659249770      0.009401\n",
-       "1  5406457556416978    4584  33.198776178      0.000218\n",
-       "2  0683522698674547    3314  99.278455039      0.000302\n",
-       "3  1020433424310577    4290  83.534331002      0.000233\n",
-       "4  8314565180058922    5841  20.741090567      0.000171"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "customer_aggregates = run_bq_query(\n",
     "    \"\"\"\n",
@@ -902,29 +534,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "metadata": {
     "id": "6460910cc6ec",
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<iframe\n",
-       "    scrolling=\"no\"\n",
-       "    width=\"100%\"\n",
-       "    height=\"545px\"\n",
-       "    src=\"iframe_figures/figure_29.html\"\n",
-       "    frameborder=\"0\"\n",
-       "    allowfullscreen\n",
-       "></iframe>\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "customer_aggregates_scatter_plot = px.scatter(\n",
     "    customer_aggregates,\n",