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Test.ipynb

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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"authorship_tag": "ABX9TyO7ueSsGfAmWiaWRfqYNjnv",
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"include_colab_link": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/Benedikt-png/Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning/blob/master/Test.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "lvZRI4qjQC_B",
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"outputId": "f292e6fe-a0ae-4a63-837b-04a4db4e715f"
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},
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"Cloning into 'Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning'...\n",
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"remote: Enumerating objects: 139, done.\u001b[K\n",
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"remote: Counting objects: 100% (132/132), done.\u001b[K\n",
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"remote: Compressing objects: 100% (60/60), done.\u001b[K\n",
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"remote: Total 139 (delta 73), reused 129 (delta 72), pack-reused 7 (from 1)\u001b[K\n",
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"Receiving objects: 100% (139/139), 5.28 MiB | 14.23 MiB/s, done.\n",
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"Resolving deltas: 100% (73/73), done.\n"
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]
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}
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],
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"source": [
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"!git clone https://github.com/Benedikt-png/Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning.git"
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]
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},
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{
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"cell_type": "code",
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"source": [
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"!git add Test.ipynb"
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],
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"metadata": {
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"id": "uaSoS0KJQXam",
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"outputId": "aff2dd9f-bd5a-4924-ee64-a4a8891bf532"
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},
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"execution_count": 2,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"fatal: not a git repository (or any of the parent directories): .git\n"
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]
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}
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]
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}
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]
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}

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