diff --git a/2-Regression/1-Tools/notebook.ipynb b/2-Regression/1-Tools/notebook.ipynb
index 6316b23b..f7cd90de 100644
--- a/2-Regression/1-Tools/notebook.ipynb
+++ b/2-Regression/1-Tools/notebook.ipynb
@@ -43,7 +43,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 32,
    "id": "6ffd05a8",
    "metadata": {},
    "outputs": [
@@ -71,7 +71,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -92,7 +92,8 @@
     "plt.xlabel('Scaled BMI')\n",
     "plt.ylabel('Diabetes Progression')\n",
     "plt.title('A graph plot showng  Diabetes Progression  Against Scaled BMI')  \n",
-    "plt.show()"
+    "plt.show()\n",
+    "#end of regression example"
    ]
   },
   {
diff --git a/2-Regression/3-Linear/notebook.ipynb b/2-Regression/3-Linear/notebook.ipynb
index aa1dc7b0..01e06088 100644
--- a/2-Regression/3-Linear/notebook.ipynb
+++ b/2-Regression/3-Linear/notebook.ipynb
@@ -16,209 +16,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "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>City Name</th>\n",
-       "      <th>Type</th>\n",
-       "      <th>Package</th>\n",
-       "      <th>Variety</th>\n",
-       "      <th>Sub Variety</th>\n",
-       "      <th>Grade</th>\n",
-       "      <th>Date</th>\n",
-       "      <th>Low Price</th>\n",
-       "      <th>High Price</th>\n",
-       "      <th>Mostly Low</th>\n",
-       "      <th>...</th>\n",
-       "      <th>Unit of Sale</th>\n",
-       "      <th>Quality</th>\n",
-       "      <th>Condition</th>\n",
-       "      <th>Appearance</th>\n",
-       "      <th>Storage</th>\n",
-       "      <th>Crop</th>\n",
-       "      <th>Repack</th>\n",
-       "      <th>Trans Mode</th>\n",
-       "      <th>Unnamed: 24</th>\n",
-       "      <th>Unnamed: 25</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>24 inch bins</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>4/29/17</td>\n",
-       "      <td>270.0</td>\n",
-       "      <td>280.0</td>\n",
-       "      <td>270.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>E</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>24 inch bins</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>5/6/17</td>\n",
-       "      <td>270.0</td>\n",
-       "      <td>280.0</td>\n",
-       "      <td>270.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>E</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>24 inch bins</td>\n",
-       "      <td>HOWDEN TYPE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9/24/16</td>\n",
-       "      <td>160.0</td>\n",
-       "      <td>160.0</td>\n",
-       "      <td>160.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>24 inch bins</td>\n",
-       "      <td>HOWDEN TYPE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>9/24/16</td>\n",
-       "      <td>160.0</td>\n",
-       "      <td>160.0</td>\n",
-       "      <td>160.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>24 inch bins</td>\n",
-       "      <td>HOWDEN TYPE</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>11/5/16</td>\n",
-       "      <td>90.0</td>\n",
-       "      <td>100.0</td>\n",
-       "      <td>90.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>N</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 26 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   City Name Type       Package      Variety Sub Variety  Grade     Date  \\\n",
-       "0  BALTIMORE  NaN  24 inch bins          NaN         NaN    NaN  4/29/17   \n",
-       "1  BALTIMORE  NaN  24 inch bins          NaN         NaN    NaN   5/6/17   \n",
-       "2  BALTIMORE  NaN  24 inch bins  HOWDEN TYPE         NaN    NaN  9/24/16   \n",
-       "3  BALTIMORE  NaN  24 inch bins  HOWDEN TYPE         NaN    NaN  9/24/16   \n",
-       "4  BALTIMORE  NaN  24 inch bins  HOWDEN TYPE         NaN    NaN  11/5/16   \n",
-       "\n",
-       "   Low Price  High Price  Mostly Low  ...  Unit of Sale Quality Condition  \\\n",
-       "0      270.0       280.0       270.0  ...           NaN     NaN       NaN   \n",
-       "1      270.0       280.0       270.0  ...           NaN     NaN       NaN   \n",
-       "2      160.0       160.0       160.0  ...           NaN     NaN       NaN   \n",
-       "3      160.0       160.0       160.0  ...           NaN     NaN       NaN   \n",
-       "4       90.0       100.0        90.0  ...           NaN     NaN       NaN   \n",
-       "\n",
-       "  Appearance Storage  Crop Repack  Trans Mode  Unnamed: 24  Unnamed: 25  \n",
-       "0        NaN     NaN   NaN      E         NaN          NaN          NaN  \n",
-       "1        NaN     NaN   NaN      E         NaN          NaN          NaN  \n",
-       "2        NaN     NaN   NaN      N         NaN          NaN          NaN  \n",
-       "3        NaN     NaN   NaN      N         NaN          NaN          NaN  \n",
-       "4        NaN     NaN   NaN      N         NaN          NaN          NaN  \n",
-       "\n",
-       "[5 rows x 26 columns]"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
@@ -227,134 +27,15 @@
     "\n",
     "pumpkins = pd.read_csv('../data/US-pumpkins.csv')\n",
     "\n",
-    "pumpkins.head()\n"
+    "pumpkins.head()\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\Paskal Sunari\\AppData\\Local\\Temp\\ipykernel_7488\\2637987050.py:9: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
-      "  day_of_year = pd.to_datetime(pumpkins['Date']).apply(lambda dt: (dt-datetime(dt.year,1,1)).days)\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>Month</th>\n",
-       "      <th>DayOfYear</th>\n",
-       "      <th>Variety</th>\n",
-       "      <th>City</th>\n",
-       "      <th>Package</th>\n",
-       "      <th>Low Price</th>\n",
-       "      <th>High Price</th>\n",
-       "      <th>Price</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>70</th>\n",
-       "      <td>9</td>\n",
-       "      <td>267</td>\n",
-       "      <td>PIE TYPE</td>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>1 1/9 bushel cartons</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>13.636364</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>71</th>\n",
-       "      <td>9</td>\n",
-       "      <td>267</td>\n",
-       "      <td>PIE TYPE</td>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>1 1/9 bushel cartons</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>16.363636</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>72</th>\n",
-       "      <td>10</td>\n",
-       "      <td>274</td>\n",
-       "      <td>PIE TYPE</td>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>1 1/9 bushel cartons</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>16.363636</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>73</th>\n",
-       "      <td>10</td>\n",
-       "      <td>274</td>\n",
-       "      <td>PIE TYPE</td>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>1 1/9 bushel cartons</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>17.0</td>\n",
-       "      <td>15.454545</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>74</th>\n",
-       "      <td>10</td>\n",
-       "      <td>281</td>\n",
-       "      <td>PIE TYPE</td>\n",
-       "      <td>BALTIMORE</td>\n",
-       "      <td>1 1/9 bushel cartons</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>15.0</td>\n",
-       "      <td>13.636364</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "    Month  DayOfYear   Variety       City               Package  Low Price  \\\n",
-       "70      9        267  PIE TYPE  BALTIMORE  1 1/9 bushel cartons       15.0   \n",
-       "71      9        267  PIE TYPE  BALTIMORE  1 1/9 bushel cartons       18.0   \n",
-       "72     10        274  PIE TYPE  BALTIMORE  1 1/9 bushel cartons       18.0   \n",
-       "73     10        274  PIE TYPE  BALTIMORE  1 1/9 bushel cartons       17.0   \n",
-       "74     10        281  PIE TYPE  BALTIMORE  1 1/9 bushel cartons       15.0   \n",
-       "\n",
-       "    High Price      Price  \n",
-       "70        15.0  13.636364  \n",
-       "71        18.0  16.363636  \n",
-       "72        18.0  16.363636  \n",
-       "73        17.0  15.454545  \n",
-       "74        15.0  13.636364  "
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "pumpkins = pumpkins[pumpkins['Package'].str.contains('bushel', case=True, regex=True)]\n",
     "\n",
@@ -391,30 +72,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x1ae64410440>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
     "plt.scatter('Month','Price',data=new_pumpkins)"
@@ -422,377 +82,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x1ae644ea490>"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "plt.scatter('DayOfYear','Price',data=new_pumpkins)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\Paskal Sunari\\AppData\\Local\\Temp\\ipykernel_7488\\3995499251.py:1: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
-      "  day_of_year = pd.to_datetime(pumpkins['Date']).apply(lambda dt: (dt-datetime(dt.year,1,1)).days)\n"
-     ]
-    }
-   ],
-   "source": [
-    "day_of_year = pd.to_datetime(pumpkins['Date']).apply(lambda dt: (dt-datetime(dt.year,1,1)).days)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "-0.14878293554077535\n",
-      "-0.16673322492745407\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(new_pumpkins['Month'].corr(new_pumpkins['Price']))\n",
-    "print(new_pumpkins['DayOfYear'].corr(new_pumpkins['Price']))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = None\n",
-    "colors = ['red', 'blue', 'green', 'yellow']\n",
-    "for i, var in enumerate(new_pumpkins['Variety'].unique()):\n",
-    "    df = new_pumpkins[new_pumpkins['Variety'] == var]\n",
-    "    ax = df.plot.scatter('DayOfYear', 'Price', ax=ax, c=colors[i], label=var)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: xlabel='Variety'>"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: xlabel='DayOfYear', ylabel='Price'>"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pie_pumpkins = new_pumpkins[new_pumpkins['Variety'] == 'PIE TYPE']\n",
-    "pie_pumpkins.plot.scatter('DayOfYear', 'Price', c='red', label='PIE TYPE')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Correlation between Day of Year and Price for PIE TYPE: -0.2669192282197318\n"
-     ]
-    }
-   ],
-   "source": [
-    "#Calculating the Correlation\n",
-    "pie_pumpkins = new_pumpkins[new_pumpkins['Variety'] == 'PIE TYPE']\n",
-    "correlation = pie_pumpkins['DayOfYear'].corr(pie_pumpkins['Price'])\n",
-    "print('Correlation between Day of Year and Price for PIE TYPE:', correlation)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "Index: 144 entries, 70 to 1630\n",
-      "Data columns (total 8 columns):\n",
-      " #   Column      Non-Null Count  Dtype  \n",
-      "---  ------      --------------  -----  \n",
-      " 0   Month       144 non-null    int32  \n",
-      " 1   DayOfYear   144 non-null    int64  \n",
-      " 2   Variety     144 non-null    object \n",
-      " 3   City        144 non-null    object \n",
-      " 4   Package     144 non-null    object \n",
-      " 5   Low Price   144 non-null    float64\n",
-      " 6   High Price  144 non-null    float64\n",
-      " 7   Price       144 non-null    float64\n",
-      "dtypes: float64(3), int32(1), int64(1), object(3)\n",
-      "memory usage: 9.6+ KB\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\Paskal Sunari\\AppData\\Local\\Temp\\ipykernel_7488\\3144308612.py:1: SettingWithCopyWarning: \n",
-      "A value is trying to be set on a copy of a slice from a DataFrame\n",
-      "\n",
-      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
-      "  pie_pumpkins.dropna(inplace=True)\n"
-     ]
-    }
-   ],
-   "source": [
-    "pie_pumpkins.dropna(inplace=True)\n",
-    "pie_pumpkins.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coefficients: [-0.01751876]\n",
-      "Intercept: 21.133734359909326\n",
-      "Score on test set: 0.10220539781539772\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sklearn.linear_model import LinearRegression\n",
-    "from sklearn.metrics import mean_squared_error\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "x = pie_pumpkins['DayOfYear'].to_numpy().reshape(-1, 1)\n",
-    "y = pie_pumpkins['Price']\n",
-    "X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=0)\n",
-    "lin_reg = LinearRegression()\n",
-    "lin_reg.fit(X_train, y_train)\n",
-    "print('Coefficients:', lin_reg.coef_)\n",
-    "print('Intercept:', lin_reg.intercept_)\n",
-    "print(\"Score on test set:\", lin_reg.score(X_test, y_test))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Mean error: 2.77 (17.2%)\n"
-     ]
-    }
-   ],
-   "source": [
-    "pred = lin_reg.predict(X_test)\n",
-    "\n",
-    "mse = np.sqrt(mean_squared_error(y_test,pred))\n",
-    "print(f'Mean error: {mse:3.3} ({mse/np.mean(pred)*100:3.3}%)')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Model determination:  0.04460606335028361\n"
-     ]
-    }
-   ],
-   "source": [
-    "score = lin_reg.score(X_train,y_train)\n",
-    "print('Model determination: ', score)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x1ae7381f9d0>"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.scatter(X_test, y_test, color='blue', label='Actual Prices')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x1ae73a71a90>"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.scatter(X_test, pred, color='red', label='Predicted Prices')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##Polynomial Regression"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Score on test set: 0.12719946902474621\n"
-     ]
-    }
-   ],
-   "source": [
-    "from sklearn.preprocessing import PolynomialFeatures\n",
-    "from sklearn.pipeline import make_pipeline\n",
-    "\n",
-    "pipeline = make_pipeline(PolynomialFeatures(2), LinearRegression())\n",
-    "\n",
-    "pipeline.fit(X_train,y_train)\n",
-    "print(\"Score on test set:\", pipeline.score(X_test, y_test))\n",
-    "pred = pipeline.predict(X_test)"
-   ]
   }
  ],
  "metadata": {