Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3977dd0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import yfinance as yf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a1ac73ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "start = '2012-01-01'\n",
    "end = '2022-12-21'\n",
    "stock = 'GOOG'\n",
    "\n",
    "data = yf.download(stock, start, end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6ebd1c4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-01-03</th>\n",
       "      <td>16.262545</td>\n",
       "      <td>16.641375</td>\n",
       "      <td>16.248346</td>\n",
       "      <td>16.573130</td>\n",
       "      <td>16.573130</td>\n",
       "      <td>147611217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-04</th>\n",
       "      <td>16.563665</td>\n",
       "      <td>16.693678</td>\n",
       "      <td>16.453827</td>\n",
       "      <td>16.644611</td>\n",
       "      <td>16.644611</td>\n",
       "      <td>114989399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-05</th>\n",
       "      <td>16.491436</td>\n",
       "      <td>16.537264</td>\n",
       "      <td>16.344486</td>\n",
       "      <td>16.413727</td>\n",
       "      <td>16.413727</td>\n",
       "      <td>131808205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-06</th>\n",
       "      <td>16.417213</td>\n",
       "      <td>16.438385</td>\n",
       "      <td>16.184088</td>\n",
       "      <td>16.189817</td>\n",
       "      <td>16.189817</td>\n",
       "      <td>108119746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-09</th>\n",
       "      <td>16.102144</td>\n",
       "      <td>16.114599</td>\n",
       "      <td>15.472754</td>\n",
       "      <td>15.503389</td>\n",
       "      <td>15.503389</td>\n",
       "      <td>233776981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-14</th>\n",
       "      <td>95.540001</td>\n",
       "      <td>97.220001</td>\n",
       "      <td>93.940002</td>\n",
       "      <td>95.309998</td>\n",
       "      <td>95.309998</td>\n",
       "      <td>26452900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-15</th>\n",
       "      <td>93.540001</td>\n",
       "      <td>94.029999</td>\n",
       "      <td>90.430000</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>28298800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-16</th>\n",
       "      <td>91.199997</td>\n",
       "      <td>91.750000</td>\n",
       "      <td>90.010002</td>\n",
       "      <td>90.860001</td>\n",
       "      <td>90.860001</td>\n",
       "      <td>48485500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-19</th>\n",
       "      <td>90.879997</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>88.925003</td>\n",
       "      <td>89.150002</td>\n",
       "      <td>89.150002</td>\n",
       "      <td>23020500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-20</th>\n",
       "      <td>88.730003</td>\n",
       "      <td>89.779999</td>\n",
       "      <td>88.040001</td>\n",
       "      <td>89.629997</td>\n",
       "      <td>89.629997</td>\n",
       "      <td>21976800</td>\n",
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       "<p>2761 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Open       High        Low      Close  Adj Close     Volume\n",
       "Date                                                                        \n",
       "2012-01-03  16.262545  16.641375  16.248346  16.573130  16.573130  147611217\n",
       "2012-01-04  16.563665  16.693678  16.453827  16.644611  16.644611  114989399\n",
       "2012-01-05  16.491436  16.537264  16.344486  16.413727  16.413727  131808205\n",
       "2012-01-06  16.417213  16.438385  16.184088  16.189817  16.189817  108119746\n",
       "2012-01-09  16.102144  16.114599  15.472754  15.503389  15.503389  233776981\n",
       "...               ...        ...        ...        ...        ...        ...\n",
       "2022-12-14  95.540001  97.220001  93.940002  95.309998  95.309998   26452900\n",
       "2022-12-15  93.540001  94.029999  90.430000  91.199997  91.199997   28298800\n",
       "2022-12-16  91.199997  91.750000  90.010002  90.860001  90.860001   48485500\n",
       "2022-12-19  90.879997  91.199997  88.925003  89.150002  89.150002   23020500\n",
       "2022-12-20  88.730003  89.779999  88.040001  89.629997  89.629997   21976800\n",
       "\n",
       "[2761 rows x 6 columns]"
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     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e4f19333",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.reset_index(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3d7853ea",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-01-03</td>\n",
       "      <td>16.262545</td>\n",
       "      <td>16.641375</td>\n",
       "      <td>16.248346</td>\n",
       "      <td>16.573130</td>\n",
       "      <td>16.573130</td>\n",
       "      <td>147611217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-01-04</td>\n",
       "      <td>16.563665</td>\n",
       "      <td>16.693678</td>\n",
       "      <td>16.453827</td>\n",
       "      <td>16.644611</td>\n",
       "      <td>16.644611</td>\n",
       "      <td>114989399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-01-05</td>\n",
       "      <td>16.491436</td>\n",
       "      <td>16.537264</td>\n",
       "      <td>16.344486</td>\n",
       "      <td>16.413727</td>\n",
       "      <td>16.413727</td>\n",
       "      <td>131808205</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-01-06</td>\n",
       "      <td>16.417213</td>\n",
       "      <td>16.438385</td>\n",
       "      <td>16.184088</td>\n",
       "      <td>16.189817</td>\n",
       "      <td>16.189817</td>\n",
       "      <td>108119746</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-01-09</td>\n",
       "      <td>16.102144</td>\n",
       "      <td>16.114599</td>\n",
       "      <td>15.472754</td>\n",
       "      <td>15.503389</td>\n",
       "      <td>15.503389</td>\n",
       "      <td>233776981</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2756</th>\n",
       "      <td>2022-12-14</td>\n",
       "      <td>95.540001</td>\n",
       "      <td>97.220001</td>\n",
       "      <td>93.940002</td>\n",
       "      <td>95.309998</td>\n",
       "      <td>95.309998</td>\n",
       "      <td>26452900</td>\n",
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       "    <tr>\n",
       "      <th>2757</th>\n",
       "      <td>2022-12-15</td>\n",
       "      <td>93.540001</td>\n",
       "      <td>94.029999</td>\n",
       "      <td>90.430000</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>28298800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2758</th>\n",
       "      <td>2022-12-16</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>91.750000</td>\n",
       "      <td>90.010002</td>\n",
       "      <td>90.860001</td>\n",
       "      <td>90.860001</td>\n",
       "      <td>48485500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2759</th>\n",
       "      <td>2022-12-19</td>\n",
       "      <td>90.879997</td>\n",
       "      <td>91.199997</td>\n",
       "      <td>88.925003</td>\n",
       "      <td>89.150002</td>\n",
       "      <td>89.150002</td>\n",
       "      <td>23020500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2760</th>\n",
       "      <td>2022-12-20</td>\n",
       "      <td>88.730003</td>\n",
       "      <td>89.779999</td>\n",
       "      <td>88.040001</td>\n",
       "      <td>89.629997</td>\n",
       "      <td>89.629997</td>\n",
       "      <td>21976800</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2761 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date       Open       High        Low      Close  Adj Close   \n",
       "0    2012-01-03  16.262545  16.641375  16.248346  16.573130  16.573130  \\\n",
       "1    2012-01-04  16.563665  16.693678  16.453827  16.644611  16.644611   \n",
       "2    2012-01-05  16.491436  16.537264  16.344486  16.413727  16.413727   \n",
       "3    2012-01-06  16.417213  16.438385  16.184088  16.189817  16.189817   \n",
       "4    2012-01-09  16.102144  16.114599  15.472754  15.503389  15.503389   \n",
       "...         ...        ...        ...        ...        ...        ...   \n",
       "2756 2022-12-14  95.540001  97.220001  93.940002  95.309998  95.309998   \n",
       "2757 2022-12-15  93.540001  94.029999  90.430000  91.199997  91.199997   \n",
       "2758 2022-12-16  91.199997  91.750000  90.010002  90.860001  90.860001   \n",
       "2759 2022-12-19  90.879997  91.199997  88.925003  89.150002  89.150002   \n",
       "2760 2022-12-20  88.730003  89.779999  88.040001  89.629997  89.629997   \n",
       "\n",
       "         Volume  \n",
       "0     147611217  \n",
       "1     114989399  \n",
       "2     131808205  \n",
       "3     108119746  \n",
       "4     233776981  \n",
       "...         ...  \n",
       "2756   26452900  \n",
       "2757   28298800  \n",
       "2758   48485500  \n",
       "2759   23020500  \n",
       "2760   21976800  \n",
       "\n",
       "[2761 rows x 7 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7e81cf47",
   "metadata": {},
   "outputs": [],
   "source": [
    "ma_100_days = data.Close.rolling(100).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "076fd307",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8, 6))\n",
    "plt.plot(ma_100_days, 'r')\n",
    "plt.plot(data.Close, 'g')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7718b510",
   "metadata": {},
   "outputs": [],
   "source": [
    "ma_200_days = data.Close.rolling(200).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5008feba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8, 6))\n",
    "plt.plot(ma_100_days, 'r')\n",
    "plt.plot(ma_200_days, 'b')\n",
    "plt.plot(data.Close, 'g')\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "33eb311a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.dropna(inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e8de745a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_train = pd.DataFrame(data.Close[0: int(len(data)*0.80)])\n",
    "data_test  = pd.DataFrame(data.Close[int(len(data)*0.80): len(data)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3526b7af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2208"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_train.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c71f2393",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "553"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_test.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3a2d2b13",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler(feature_range = (0,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "69dbffaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_train_scale = scaler.fit_transform(data_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "29c3dda9",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = []\n",
    "y = []\n",
    "\n",
    "for i in range(100, data_train_scale.shape[0]):\n",
    "    x.append(data_train_scale[i - 100: i])\n",
    "    y.append(data_train_scale[i,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "197e6a9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = np.array(x), np.array(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "662d3ac5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.layers import Dense, Dropout, LSTM\n",
    "from keras.models import Sequential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "fc518275",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Sequential()\n",
    "model.add(LSTM(units = 50, activation = 'relu', return_sequences = True, input_shape = ((x.shape[1],1))))\n",
    "model.add(Dropout(0.2))\n",
    "\n",
    "model.add(LSTM(units = 60, activation = 'relu', return_sequences = True))\n",
    "model.add(Dropout(0.3))\n",
    "\n",
    "model.add(LSTM(units = 80, activation = 'relu', return_sequences = True))\n",
    "model.add(Dropout(0.4))\n",
    "\n",
    "model.add(LSTM(units = 120, activation = 'relu'))\n",
    "model.add(Dropout(0.5))\n",
    "\n",
    "model.add(Dense(units = 1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "cfb82e27",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile( optimizer = 'adam', loss = 'mean_squared_error')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "04d92eee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "66/66 [==============================] - 14s 133ms/step - loss: 0.0269\n",
      "Epoch 2/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0058\n",
      "Epoch 3/50\n",
      "66/66 [==============================] - 9s 138ms/step - loss: 0.0047\n",
      "Epoch 4/50\n",
      "66/66 [==============================] - 9s 135ms/step - loss: 0.0050\n",
      "Epoch 5/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0049\n",
      "Epoch 6/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0045\n",
      "Epoch 7/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0041\n",
      "Epoch 8/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0040\n",
      "Epoch 9/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0035\n",
      "Epoch 10/50\n",
      "66/66 [==============================] - 9s 139ms/step - loss: 0.0034\n",
      "Epoch 11/50\n",
      "66/66 [==============================] - 9s 141ms/step - loss: 0.0034\n",
      "Epoch 12/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0035\n",
      "Epoch 13/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0035\n",
      "Epoch 14/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0033\n",
      "Epoch 15/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0029\n",
      "Epoch 16/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0031\n",
      "Epoch 17/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0031\n",
      "Epoch 18/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0027\n",
      "Epoch 19/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0028\n",
      "Epoch 20/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0025\n",
      "Epoch 21/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0030\n",
      "Epoch 22/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0024\n",
      "Epoch 23/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0026\n",
      "Epoch 24/50\n",
      "66/66 [==============================] - 9s 135ms/step - loss: 0.0021\n",
      "Epoch 25/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0024\n",
      "Epoch 26/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0024\n",
      "Epoch 27/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0022\n",
      "Epoch 28/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0022\n",
      "Epoch 29/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0021\n",
      "Epoch 30/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0024\n",
      "Epoch 31/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0020\n",
      "Epoch 32/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0021\n",
      "Epoch 33/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0020\n",
      "Epoch 34/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0021\n",
      "Epoch 35/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0021\n",
      "Epoch 36/50\n",
      "66/66 [==============================] - 9s 131ms/step - loss: 0.0020\n",
      "Epoch 37/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0020\n",
      "Epoch 38/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0019\n",
      "Epoch 39/50\n",
      "66/66 [==============================] - 9s 132ms/step - loss: 0.0020\n",
      "Epoch 40/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0019\n",
      "Epoch 41/50\n",
      "66/66 [==============================] - 9s 134ms/step - loss: 0.0018\n",
      "Epoch 42/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0020\n",
      "Epoch 43/50\n",
      "66/66 [==============================] - 9s 136ms/step - loss: 0.0018\n",
      "Epoch 44/50\n",
      "66/66 [==============================] - 9s 138ms/step - loss: 0.0020\n",
      "Epoch 45/50\n",
      "66/66 [==============================] - 9s 134ms/step - loss: 0.0020\n",
      "Epoch 46/50\n",
      "66/66 [==============================] - 9s 135ms/step - loss: 0.0018\n",
      "Epoch 47/50\n",
      "66/66 [==============================] - 9s 141ms/step - loss: 0.0021\n",
      "Epoch 48/50\n",
      "66/66 [==============================] - 9s 137ms/step - loss: 0.0019\n",
      "Epoch 49/50\n",
      "66/66 [==============================] - 9s 133ms/step - loss: 0.0019\n",
      "Epoch 50/50\n",
      "66/66 [==============================] - 10s 145ms/step - loss: 0.0019\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.History at 0x2b5976e8090>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(x, y, epochs = 50, batch_size = 32, verbose = 1 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "92b2263e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_3\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " lstm_8 (LSTM)               (None, 100, 50)           10400     \n",
      "                                                                 \n",
      " dropout_8 (Dropout)         (None, 100, 50)           0         \n",
      "                                                                 \n",
      " lstm_9 (LSTM)               (None, 100, 60)           26640     \n",
      "                                                                 \n",
      " dropout_9 (Dropout)         (None, 100, 60)           0         \n",
      "                                                                 \n",
      " lstm_10 (LSTM)              (None, 100, 80)           45120     \n",
      "                                                                 \n",
      " dropout_10 (Dropout)        (None, 100, 80)           0         \n",
      "                                                                 \n",
      " lstm_11 (LSTM)              (None, 120)               96480     \n",
      "                                                                 \n",
      " dropout_11 (Dropout)        (None, 120)               0         \n",
      "                                                                 \n",
      " dense_2 (Dense)             (None, 1)                 121       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 178761 (698.29 KB)\n",
      "Trainable params: 178761 (698.29 KB)\n",
      "Non-trainable params: 0 (0.00 Byte)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "44ee2551",
   "metadata": {},
   "outputs": [],
   "source": [
    "pas_100_days = data_train.tail(100)\n",
    "\n",
    "data_test = pd.concat((pas_100_days, data_test), ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9ad54121",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_test_scale = scaler.fit_transform(data_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "bb0baba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = []\n",
    "y = []\n",
    "\n",
    "for i in range(100, data_test_scale.shape[0]):\n",
    "    x.append(data_test_scale[i - 100: i])\n",
    "    y.append(data_test_scale[i,0])\n",
    "    \n",
    "x, y = np.array(x), np.array(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "17a92dc6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18/18 [==============================] - 1s 41ms/step\n"
     ]
    }
   ],
   "source": [
    "y_predict = model.predict(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "becc0f85",
   "metadata": {},
   "outputs": [],
   "source": [
    "scale = 1/scaler.scale_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "c8f042b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_predict = y_predict * scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "addcffb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "y = y*scale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "85504f6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "plt.plot(y_predict, 'r', label = 'Predicted Price')\n",
    "plt.plot(y, 'g', label = 'Original Price')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "f452dc2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save('Stock Prediction Model.keras')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5b282c8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}