Tensorflow_basics.ipynb

{
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        "id": "view-in-github",
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        "<a href=\"https://colab.research.google.com/github/adarshnitt/Deep-Learning/blob/main/Tensorflow_basics.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
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        "id": "gRPTVKVYGE_3",
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          "base_uri": "https://localhost:8080/"
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        "outputId": "ca0cb550-0d8f-4e73-f7b4-7933df150c14"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ],
      "source": [
        "# !pip install tensorflow-gpu # when u have to run over gpu\n",
        "!pip install tensorflow"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "YzSdegwqGFBn"
      },
      "outputs": [],
      "source": [
        "# tensorflow  written in Python,cuda([parallel computting])\n",
        "# Motivation: https://youtu.be/uGYJuOyIvzs"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# scaler: directionless\n",
        "# vector: with directionx\n",
        "\n",
        "[-]                               1-D(Scaler) <br>\n",
        "[---------]                       2-D(vector)\n",
        "\n",
        "[[---------]\n",
        " [---------]\n",
        " [---------]]                     N-D(Matrix)\n",
        " \n",
        "<b>Tensor</b>:Mathmatical object, <h3>multidimentional</h3> array <br>\n",
        "  1-Rank:(Scaler,vector,Matrix) <br>\n",
        "  2- Shape: no of row and column <br>\n",
        "  3- type:  data type assign to tensor elemnts<br>\n",
        " <b> Flow <b>:  sequence of mathmatical operations <br><br><br>\n",
        "    code> graph/ nodes(mathmatical operations)>session>implementation.\n",
        " "
      ],
      "metadata": {
        "id": "x-xKXUnvrMWj"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lkzsuM_HGFEz"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nCFguUlWGFGZ"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ANpIRv7jGFH9"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KKkj_gL2GFJz"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hDhljQ26GFNM"
      },
      "outputs": [],
      "source": [
        ""
      ]
    }
  ],
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    "colab": {
      "name": "Tensorflow basics.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyPv8nPM2bEtv4rEt3sgr6fd",
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      "display_name": "Python 3",
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    "language_info": {
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