Stock_Market_Prediction_Model_Creation.ipynb

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            "/usr/local/lib/python3.10/dist-packages/yfinance/base.py:48: FutureWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
            "  _empty_series = pd.Series()\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import yfinance as yf"
      ]
    },
    {
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          "text": [
            "\r[*********************100%%**********************]  1 of 1 completed\n"
          ]
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      "source": [
        "start = '2012-01-01'\n",
        "end = '2024-01-01'\n",
        "stock = 'INFY'\n",
        "\n",
        "data = yf.download(stock, start, end)"
      ]
    },
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        "data.reset_index(inplace=True)"
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              "           Date       Open       High        Low      Close  Adj Close  \\\n",
              "0    2012-01-03   6.706250   6.805000   6.662500   6.681250   4.987726   \n",
              "1    2012-01-04   6.700000   6.757500   6.638750   6.650000   4.964397   \n",
              "2    2012-01-05   6.651250   6.793750   6.640000   6.751250   5.039983   \n",
              "3    2012-01-06   6.726250   6.750000   6.640000   6.740000   5.031584   \n",
              "4    2012-01-09   6.771250   6.932500   6.752500   6.917500   5.164092   \n",
              "...         ...        ...        ...        ...        ...        ...   \n",
              "3013 2023-12-22  18.700001  18.889999  18.639999  18.760000  18.760000   \n",
              "3014 2023-12-26  18.639999  18.670000  18.370001  18.450001  18.450001   \n",
              "3015 2023-12-27  18.639999  18.680000  18.450001  18.600000  18.600000   \n",
              "3016 2023-12-28  18.610001  18.680000  18.530001  18.559999  18.559999   \n",
              "3017 2023-12-29  18.500000  18.530001  18.320000  18.379999  18.379999   \n",
              "\n",
              "        Volume  \n",
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              "3014   3866200  \n",
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              "      <th>Date</th>\n",
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              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_3adb2e00-0c68-4109-bce0-0659c0ec7086 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('data');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "id": "8a478e83-6aee-4809-9405-be6f8b65b16a",
      "metadata": {
        "id": "8a478e83-6aee-4809-9405-be6f8b65b16a"
      },
      "outputs": [],
      "source": [
        "ma_100_days = data.Close.rolling(100).mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "fc840124-ef3e-40b0-9e74-aa5a174c4c50",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "id": "fc840124-ef3e-40b0-9e74-aa5a174c4c50",
        "outputId": "915698bc-bebf-44e6-8cc1-a6c91e443f8a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "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": 7,
      "id": "1158c05f-1a2c-41f8-8add-85720074cdcd",
      "metadata": {
        "id": "1158c05f-1a2c-41f8-8add-85720074cdcd"
      },
      "outputs": [],
      "source": [
        "ma_200_days = data.Close.rolling(200).mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "id": "97a1b79b-2302-43d7-883a-a0a255c864bf",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "id": "97a1b79b-2302-43d7-883a-a0a255c864bf",
        "outputId": "d5a3a091-6386-4033-ced3-9d42e8090d63"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "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": 9,
      "id": "0ac073de-1a30-487c-a1f8-c809cbba06db",
      "metadata": {
        "id": "0ac073de-1a30-487c-a1f8-c809cbba06db"
      },
      "outputs": [],
      "source": [
        "data.dropna(inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "64246466-177b-46f9-b4eb-6ee5005bfd6b",
      "metadata": {
        "id": "64246466-177b-46f9-b4eb-6ee5005bfd6b"
      },
      "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": 11,
      "id": "0f4c0b4b-2b5e-4f62-bd84-47a86ed3da3e",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0f4c0b4b-2b5e-4f62-bd84-47a86ed3da3e",
        "outputId": "42c2a651-cd08-4593-bbe3-3a3a7e11f1a7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2414"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "data_train.shape[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "id": "0a609554-633d-4edf-abc1-21bd874a3cd1",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0a609554-633d-4edf-abc1-21bd874a3cd1",
        "outputId": "ca21e874-950a-408d-f665-f8f8dbf90bc6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "604"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "data_test.shape[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "id": "d5144e93-eab7-479f-9fde-9bf8c5786dc6",
      "metadata": {
        "id": "d5144e93-eab7-479f-9fde-9bf8c5786dc6"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import MinMaxScaler\n",
        "scaler = MinMaxScaler(feature_range=(0,1))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "id": "4c2793bd-1def-45f7-8fd2-9115eed1c2c1",
      "metadata": {
        "id": "4c2793bd-1def-45f7-8fd2-9115eed1c2c1"
      },
      "outputs": [],
      "source": [
        "data_train_scale = scaler.fit_transform(data_train)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "id": "d55d63c2-132a-40b5-9398-e576ceba14fd",
      "metadata": {
        "id": "d55d63c2-132a-40b5-9398-e576ceba14fd"
      },
      "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])\n",
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "id": "998369e6-f1ad-4cf5-af58-0aa5b7aa315c",
      "metadata": {
        "id": "998369e6-f1ad-4cf5-af58-0aa5b7aa315c"
      },
      "outputs": [],
      "source": [
        "x, y = np.array(x), np.array(y)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "3c9c6717-e792-4206-960f-0689203555ca",
      "metadata": {
        "id": "3c9c6717-e792-4206-960f-0689203555ca"
      },
      "outputs": [],
      "source": [
        "from keras.layers import Dense, Dropout, LSTM\n",
        "from keras.models import Sequential"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "id": "14867cd4-c1ed-4cf9-b339-245bfaec0852",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "14867cd4-c1ed-4cf9-b339-245bfaec0852",
        "outputId": "7f2119e2-e786-40a9-f132-acbb9409112e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:tensorflow:Layer lstm will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.\n",
            "WARNING:tensorflow:Layer lstm_1 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.\n",
            "WARNING:tensorflow:Layer lstm_2 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.\n",
            "WARNING:tensorflow:Layer lstm_3 will not use cuDNN kernels since it doesn't meet the criteria. It will use a generic GPU kernel as fallback when running on GPU.\n"
          ]
        }
      ],
      "source": [
        "model = Sequential()\n",
        "model.add(LSTM(units = 50, activation = 'relu', return_sequences = True,\n",
        "               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))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "id": "c69edcc2-b11d-4702-8a6c-f6a6e677e79a",
      "metadata": {
        "id": "c69edcc2-b11d-4702-8a6c-f6a6e677e79a"
      },
      "outputs": [],
      "source": [
        "model.compile(optimizer = 'adam', loss = 'mean_squared_error')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "id": "f36e439a-0106-4108-9630-7cdd7e5428e4",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f36e439a-0106-4108-9630-7cdd7e5428e4",
        "outputId": "4d5ae8e8-94a1-4547-f823-548b8be3c2f9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/50\n",
            "73/73 [==============================] - 48s 541ms/step - loss: 0.0175\n",
            "Epoch 2/50\n",
            "73/73 [==============================] - 37s 511ms/step - loss: 0.0046\n",
            "Epoch 3/50\n",
            "73/73 [==============================] - 37s 513ms/step - loss: 0.0039\n",
            "Epoch 4/50\n",
            "73/73 [==============================] - 37s 510ms/step - loss: 0.0032\n",
            "Epoch 5/50\n",
            "73/73 [==============================] - 38s 524ms/step - loss: 0.0035\n",
            "Epoch 6/50\n",
            "73/73 [==============================] - 36s 496ms/step - loss: 0.0031\n",
            "Epoch 7/50\n",
            "73/73 [==============================] - 38s 515ms/step - loss: 0.0032\n",
            "Epoch 8/50\n",
            "73/73 [==============================] - 37s 510ms/step - loss: 0.0026\n",
            "Epoch 9/50\n",
            "73/73 [==============================] - 37s 508ms/step - loss: 0.0024\n",
            "Epoch 10/50\n",
            "73/73 [==============================] - 37s 505ms/step - loss: 0.0028\n",
            "Epoch 11/50\n",
            "73/73 [==============================] - 37s 506ms/step - loss: 0.0021\n",
            "Epoch 12/50\n",
            "73/73 [==============================] - 37s 508ms/step - loss: 0.0022\n",
            "Epoch 13/50\n",
            "73/73 [==============================] - 37s 506ms/step - loss: 0.0021\n",
            "Epoch 14/50\n",
            "73/73 [==============================] - 36s 489ms/step - loss: 0.0022\n",
            "Epoch 15/50\n",
            "73/73 [==============================] - 36s 482ms/step - loss: 0.0021\n",
            "Epoch 16/50\n",
            "73/73 [==============================] - 36s 491ms/step - loss: 0.0021\n",
            "Epoch 17/50\n",
            "73/73 [==============================] - 36s 493ms/step - loss: 0.0018\n",
            "Epoch 18/50\n",
            "73/73 [==============================] - 36s 492ms/step - loss: 0.0019\n",
            "Epoch 19/50\n",
            "73/73 [==============================] - 37s 494ms/step - loss: 0.0020\n",
            "Epoch 20/50\n",
            "73/73 [==============================] - 36s 491ms/step - loss: 0.0018\n",
            "Epoch 21/50\n",
            "73/73 [==============================] - 36s 492ms/step - loss: 0.0018\n",
            "Epoch 22/50\n",
            "73/73 [==============================] - 37s 500ms/step - loss: 0.0017\n",
            "Epoch 23/50\n",
            "73/73 [==============================] - 36s 497ms/step - loss: 0.0018\n",
            "Epoch 24/50\n",
            "73/73 [==============================] - 36s 494ms/step - loss: 0.0017\n",
            "Epoch 25/50\n",
            "73/73 [==============================] - 36s 500ms/step - loss: 0.0017\n",
            "Epoch 26/50\n",
            "73/73 [==============================] - 37s 509ms/step - loss: 0.0018\n",
            "Epoch 27/50\n",
            "73/73 [==============================] - 36s 494ms/step - loss: 0.0014\n",
            "Epoch 28/50\n",
            "73/73 [==============================] - 36s 493ms/step - loss: 0.0015\n",
            "Epoch 29/50\n",
            "73/73 [==============================] - 36s 492ms/step - loss: 0.0018\n",
            "Epoch 30/50\n",
            "73/73 [==============================] - 35s 484ms/step - loss: 0.0018\n",
            "Epoch 31/50\n",
            "73/73 [==============================] - 35s 482ms/step - loss: 0.0017\n",
            "Epoch 32/50\n",
            "73/73 [==============================] - 35s 478ms/step - loss: 0.0016\n",
            "Epoch 33/50\n",
            "73/73 [==============================] - 37s 504ms/step - loss: 0.0015\n",
            "Epoch 34/50\n",
            "73/73 [==============================] - 36s 484ms/step - loss: 0.0016\n",
            "Epoch 35/50\n",
            "73/73 [==============================] - 36s 493ms/step - loss: 0.0016\n",
            "Epoch 36/50\n",
            "73/73 [==============================] - 36s 494ms/step - loss: 0.0016\n",
            "Epoch 37/50\n",
            "73/73 [==============================] - 36s 491ms/step - loss: 0.0016\n",
            "Epoch 38/50\n",
            "73/73 [==============================] - 35s 477ms/step - loss: 0.0017\n",
            "Epoch 39/50\n",
            "73/73 [==============================] - 35s 473ms/step - loss: 0.0017\n",
            "Epoch 40/50\n",
            "73/73 [==============================] - 35s 479ms/step - loss: 0.0016\n",
            "Epoch 41/50\n",
            "73/73 [==============================] - 35s 479ms/step - loss: 0.0015\n",
            "Epoch 42/50\n",
            "73/73 [==============================] - 35s 483ms/step - loss: 0.0016\n",
            "Epoch 43/50\n",
            "73/73 [==============================] - 35s 482ms/step - loss: 0.0014\n",
            "Epoch 44/50\n",
            "73/73 [==============================] - 36s 488ms/step - loss: 0.0015\n",
            "Epoch 45/50\n",
            "73/73 [==============================] - 36s 490ms/step - loss: 0.0016\n",
            "Epoch 46/50\n",
            "73/73 [==============================] - 36s 488ms/step - loss: 0.0014\n",
            "Epoch 47/50\n",
            "73/73 [==============================] - 37s 510ms/step - loss: 0.0015\n",
            "Epoch 48/50\n",
            "73/73 [==============================] - 36s 491ms/step - loss: 0.0015\n",
            "Epoch 49/50\n",
            "73/73 [==============================] - 35s 485ms/step - loss: 0.0014\n",
            "Epoch 50/50\n",
            "73/73 [==============================] - 36s 490ms/step - loss: 0.0015\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7b4477903eb0>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "model.fit(x,y, epochs = 50, batch_size =32, verbose =1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "id": "62f9decd-83a6-4c03-8963-dc3298b2a104",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "62f9decd-83a6-4c03-8963-dc3298b2a104",
        "outputId": "e51016f5-5abb-4b49-abb8-d0a756b58505"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " lstm (LSTM)                 (None, 100, 50)           10400     \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 100, 50)           0         \n",
            "                                                                 \n",
            " lstm_1 (LSTM)               (None, 100, 60)           26640     \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 100, 60)           0         \n",
            "                                                                 \n",
            " lstm_2 (LSTM)               (None, 100, 80)           45120     \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 100, 80)           0         \n",
            "                                                                 \n",
            " lstm_3 (LSTM)               (None, 120)               96480     \n",
            "                                                                 \n",
            " dropout_3 (Dropout)         (None, 120)               0         \n",
            "                                                                 \n",
            " dense (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": 22,
      "id": "89cf9dc7-4e14-4c80-82bc-d6dcac8c98a2",
      "metadata": {
        "id": "89cf9dc7-4e14-4c80-82bc-d6dcac8c98a2"
      },
      "outputs": [],
      "source": [
        "pas_100_days = data_train.tail(100)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "id": "67ef7a1e-63cc-4874-9b61-634026572822",
      "metadata": {
        "id": "67ef7a1e-63cc-4874-9b61-634026572822"
      },
      "outputs": [],
      "source": [
        "data_test = pd.concat([pas_100_days, data_test], ignore_index=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "id": "7a0512e4-0eaf-4137-b61d-8bb0e48ca041",
      "metadata": {
        "id": "7a0512e4-0eaf-4137-b61d-8bb0e48ca041"
      },
      "outputs": [],
      "source": [
        "data_test_scale  =  scaler.fit_transform(data_test)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "id": "536de9d0-2cc7-41dd-b500-affd3e3fec9d",
      "metadata": {
        "id": "536de9d0-2cc7-41dd-b500-affd3e3fec9d"
      },
      "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",
        "x, y = np.array(x), np.array(y)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# score = model.evaluate(x, y, verbose=0)\n",
        "# print('Test loss:', score)\n",
        "# print('Test accuracy:', score)\n",
        "score = model.evaluate(x, y, verbose=0)\n",
        "\n",
        "print(f'Test loss: {score} / Test accuracy: {score}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tUYL80HaI7be",
        "outputId": "6c8beff8-913d-44ad-c7bf-1f9bcdd55889"
      },
      "id": "tUYL80HaI7be",
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Test loss: 24.94234275817871 / Test accuracy: 24.94234275817871\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "id": "4602f57f-8832-4bf6-a50e-bb5164ff7872",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4602f57f-8832-4bf6-a50e-bb5164ff7872",
        "outputId": "e5d84dc7-b92f-4a85-cbeb-62ea486d5e98"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "19/19 [==============================] - 2s 62ms/step\n"
          ]
        }
      ],
      "source": [
        "y_predict = model.predict(x)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "id": "ca2d2d64-b69a-4eb3-b4f6-5356bfb5b74a",
      "metadata": {
        "id": "ca2d2d64-b69a-4eb3-b4f6-5356bfb5b74a"
      },
      "outputs": [],
      "source": [
        "scale =1/scaler.scale_"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "id": "b3e3794a-785d-4ac8-96a3-70fab6259f1c",
      "metadata": {
        "id": "b3e3794a-785d-4ac8-96a3-70fab6259f1c"
      },
      "outputs": [],
      "source": [
        "y_predict = y_predict*scale"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "id": "5acb458b-7488-4860-9ccd-8999d67510f7",
      "metadata": {
        "id": "5acb458b-7488-4860-9ccd-8999d67510f7"
      },
      "outputs": [],
      "source": [
        "y = y*scale"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I_tcRfgTLtY7",
        "outputId": "04a3a35f-fabe-4d3e-fdcb-0698015b3dc1"
      },
      "id": "I_tcRfgTLtY7",
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Test loss: 24.94234275817871\n",
            "Test accuracy: 24.94234275817871\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "id": "6ab280be-9494-4ea1-baf2-45fc38130366",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 696
        },
        "id": "6ab280be-9494-4ea1-baf2-45fc38130366",
        "outputId": "80f3a8fb-c71a-4c41-e3df-cdf022b96647"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "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": 49,
      "id": "22143940-722e-4c05-8b46-d2f7d9abb882",
      "metadata": {
        "id": "22143940-722e-4c05-8b46-d2f7d9abb882"
      },
      "outputs": [],
      "source": [
        "model.save('Stock Predicti Model.keras')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "id": "bd3bc001-da88-44ba-85d1-9b72ebfde3a6",
      "metadata": {
        "id": "bd3bc001-da88-44ba-85d1-9b72ebfde3a6"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.11.6"
    },
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "accelerator": "GPU"
  },
  "nbformat": 4,
  "nbformat_minor": 5
}