Meta_LSTM.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyN4obWDnjeaMlTiUVcw2uFV",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/moebqr/Meta-LSTM-Prediction/blob/main/Meta_LSTM.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# LSTM Model for Meta Stock Price Prediction\n",
        "## Based on Meta Stock Price Data from 2013/01/01 to 2024/01/01"
      ],
      "metadata": {
        "id": "L2IXVbkVu5tH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Installing the necessary libraries"
      ],
      "metadata": {
        "id": "StEYcyLiu12Q"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vvZmzTcAuddh",
        "outputId": "fdb30b53-4be9-4b47-cd73-4701d44f0006"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ],
      "source": [
        "!pip install yfinance tensorflow"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import yfinance as yf\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import LSTM, Dense, Dropout"
      ],
      "metadata": {
        "id": "GSIsM2TDvglC"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Load Meta stock price data"
      ],
      "metadata": {
        "id": "EqNpoLsPwXIs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "stock_symbol = 'META'\n",
        "start_date = '2013-01-01'\n",
        "end_date = '2024-01-01'\n",
        "data = yf.download(stock_symbol, start=start_date, end=end_date)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pugjRAAuv4qu",
        "outputId": "cfe3316d-1e5b-4bae-81d4-d40def0e7a5d"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r[*********************100%%**********************]  1 of 1 completed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Preprocess the data"
      ],
      "metadata": {
        "id": "k0fqSxwVwZmP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data = data[['Close']]\n",
        "scaler = MinMaxScaler(feature_range=(0, 1))\n",
        "scaled_data = scaler.fit_transform(data)"
      ],
      "metadata": {
        "id": "xXSNAJIPwhXi"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Creating training and testing datasets"
      ],
      "metadata": {
        "id": "blvwFJzCw0b-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "training_data_len = int(np.ceil(len(scaled_data) * 0.8))\n",
        "train_data = scaled_data[0:int(training_data_len), :]\n",
        "test_data = scaled_data[training_data_len - 60:, :]"
      ],
      "metadata": {
        "id": "eFab7FMOw7q_"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Creating the dataset"
      ],
      "metadata": {
        "id": "fy4uFZwbxqkB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x_train, y_train = [], []\n",
        "for i in range(60, len(train_data)):\n",
        "    x_train.append(train_data[i-60:i, 0])\n",
        "    y_train.append(train_data[i, 0])\n",
        "x_train, y_train = np.array(x_train), np.array(y_train)\n",
        "x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], 1))"
      ],
      "metadata": {
        "id": "ctp5Thnxxtvs"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Create the testing dataset"
      ],
      "metadata": {
        "id": "H5sUkLvfxykw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x_test, y_test = [], []\n",
        "for i in range(60, len(test_data)):\n",
        "    x_test.append(test_data[i-60:i, 0])\n",
        "    y_test.append(test_data[i, 0])\n",
        "x_test, y_test = np.array(x_test), np.array(y_test)\n",
        "x_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], 1))"
      ],
      "metadata": {
        "id": "ZKtNs5Fux3-K"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Build the LSTM Model"
      ],
      "metadata": {
        "id": "8FOesEfQx8JS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = Sequential()\n",
        "model.add(LSTM(units=50, return_sequences=True, input_shape=(x_train.shape[1], 1)))\n",
        "model.add(LSTM(units=50, return_sequences=False))\n",
        "model.add(Dense(units=25))\n",
        "model.add(Dense(units=1))"
      ],
      "metadata": {
        "id": "LyFtBCBOx-RC"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Compile the model"
      ],
      "metadata": {
        "id": "MIdCG2W0yDLT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(optimizer='adam', loss='mean_squared_error')"
      ],
      "metadata": {
        "id": "SFObN_YQyFx-"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Train the model"
      ],
      "metadata": {
        "id": "qMseHh3fyImq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(x_train, y_train, batch_size=1, epochs=1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AGGPPvjHyKTT",
        "outputId": "7f152b01-f21e-4221-ba87-e63417102929"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2155/2155 [==============================] - 76s 33ms/step - loss: 0.0014\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7ee7037135e0>"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Make Predictions"
      ],
      "metadata": {
        "id": "6emYLfX6yjSg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "predictions = model.predict(x_test)\n",
        "predictions = scaler.inverse_transform(predictions)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pooiwO3Byls8",
        "outputId": "671ab284-acbe-4b94-c4db-a959b43c83dd"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "18/18 [==============================] - 2s 17ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Plot the results"
      ],
      "metadata": {
        "id": "i3zEs15tysST"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train = data[:training_data_len]\n",
        "valid = data[training_data_len:]\n",
        "valid['Predictions'] = predictions\n",
        "\n",
        "plt.figure(figsize=(16,8))\n",
        "plt.title('LSTM Model')\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Close Price USD ($)')\n",
        "plt.plot(train['Close'])\n",
        "plt.plot(valid[['Close', 'Predictions']])\n",
        "plt.legend(['Train', 'Val', 'Predictions'], loc='lower right')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 822
        },
        "id": "f0CibvGAyuAe",
        "outputId": "85d8c9ab-9fdc-43e4-a5a5-7c73d3e5e29d"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-13-8ec88faa450b>:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\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",
            "  valid['Predictions'] = predictions\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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}