C1_W1_Lab_hello_world_nn.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "C1_W1_Lab-hello_world_nn.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOHhDqcghsCxdZYeElEEPBU",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Steve-YJ/Google-ML-Bootcamp-2021-Kor/blob/main/C1_W1_Lab_hello_world_nn.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "1lMKEVoPBx2G",
        "outputId": "6e5f12be-68df-4197-e06f-ce11cae17af3"
      },
      "source": [
        "import tensorflow as tf\n",
        "print(tf.__version__)"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2.6.0'"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KGl4wi8pCbbQ"
      },
      "source": [
        "**Note** : You can run notebook using TensorFlow 2.5.0"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "nBUTKD6aCu8S",
        "outputId": "c2a816b3-0747-4ccf-c0d4-77965a210216"
      },
      "source": [
        "! pip install tensorflow==2.5.0"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting tensorflow==2.5.0\n",
            "  Downloading tensorflow-2.5.0-cp37-cp37m-manylinux2010_x86_64.whl (454.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 454.3 MB 14 kB/s \n",
            "\u001b[?25hRequirement already satisfied: h5py~=3.1.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (3.1.0)\n",
            "Collecting keras-nightly~=2.5.0.dev\n",
            "  Downloading keras_nightly-2.5.0.dev2021032900-py2.py3-none-any.whl (1.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2 MB 27.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: typing-extensions~=3.7.4 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (3.7.4.3)\n",
            "Requirement already satisfied: google-pasta~=0.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (0.2.0)\n",
            "Requirement already satisfied: protobuf>=3.9.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (3.17.3)\n",
            "Requirement already satisfied: opt-einsum~=3.3.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (3.3.0)\n",
            "Requirement already satisfied: numpy~=1.19.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.19.5)\n",
            "Requirement already satisfied: wrapt~=1.12.1 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.12.1)\n",
            "Requirement already satisfied: astunparse~=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.6.3)\n",
            "Requirement already satisfied: flatbuffers~=1.12.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.12)\n",
            "Collecting tensorflow-estimator<2.6.0,>=2.5.0rc0\n",
            "  Downloading tensorflow_estimator-2.5.0-py2.py3-none-any.whl (462 kB)\n",
            "\u001b[K     |████████████████████████████████| 462 kB 47.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: six~=1.15.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.15.0)\n",
            "Requirement already satisfied: absl-py~=0.10 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (0.12.0)\n",
            "Requirement already satisfied: wheel~=0.35 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (0.37.0)\n",
            "Collecting grpcio~=1.34.0\n",
            "  Downloading grpcio-1.34.1-cp37-cp37m-manylinux2014_x86_64.whl (4.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 4.0 MB 30.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: gast==0.4.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (0.4.0)\n",
            "Requirement already satisfied: termcolor~=1.1.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.1.0)\n",
            "Requirement already satisfied: tensorboard~=2.5 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (2.6.0)\n",
            "Requirement already satisfied: keras-preprocessing~=1.1.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow==2.5.0) (1.1.2)\n",
            "Requirement already satisfied: cached-property in /usr/local/lib/python3.7/dist-packages (from h5py~=3.1.0->tensorflow==2.5.0) (1.5.2)\n",
            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (57.4.0)\n",
            "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (1.8.0)\n",
            "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (0.6.1)\n",
            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (2.23.0)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (0.4.6)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (1.0.1)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (3.3.4)\n",
            "Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.5->tensorflow==2.5.0) (1.35.0)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.5->tensorflow==2.5.0) (4.2.4)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.5->tensorflow==2.5.0) (0.2.8)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.5->tensorflow==2.5.0) (4.7.2)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.5->tensorflow==2.5.0) (1.3.0)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from markdown>=2.6.8->tensorboard~=2.5->tensorflow==2.5.0) (4.8.1)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard~=2.5->tensorflow==2.5.0) (0.4.8)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.5->tensorflow==2.5.0) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.5->tensorflow==2.5.0) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.5->tensorflow==2.5.0) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.5->tensorflow==2.5.0) (2021.5.30)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.5->tensorflow==2.5.0) (3.1.1)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->markdown>=2.6.8->tensorboard~=2.5->tensorflow==2.5.0) (3.6.0)\n",
            "Installing collected packages: grpcio, tensorflow-estimator, keras-nightly, tensorflow\n",
            "  Attempting uninstall: grpcio\n",
            "    Found existing installation: grpcio 1.41.0\n",
            "    Uninstalling grpcio-1.41.0:\n",
            "      Successfully uninstalled grpcio-1.41.0\n",
            "  Attempting uninstall: tensorflow-estimator\n",
            "    Found existing installation: tensorflow-estimator 2.6.0\n",
            "    Uninstalling tensorflow-estimator-2.6.0:\n",
            "      Successfully uninstalled tensorflow-estimator-2.6.0\n",
            "  Attempting uninstall: tensorflow\n",
            "    Found existing installation: tensorflow 2.6.0\n",
            "    Uninstalling tensorflow-2.6.0:\n",
            "      Successfully uninstalled tensorflow-2.6.0\n",
            "Successfully installed grpcio-1.34.1 keras-nightly-2.5.0.dev2021032900 tensorflow-2.5.0 tensorflow-estimator-2.5.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "tensorflow"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uK4V8NwgCynH",
        "outputId": "dc737a20-c257-4367-fd02-ef42b40b0a1c"
      },
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "from tensorflow import keras\n",
        "\n",
        "print(tf.__version__)"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2.5.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wlH9S6G_C5vh"
      },
      "source": [
        "## Define and Compile the Neural Network"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hSqEhWVYC-BW"
      },
      "source": [
        "model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])])"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yHVkUdx2DeQ6"
      },
      "source": [
        "model.compile(optimizer='sgd', loss='mean_squared_error')"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZCh1K4XTC-Dd"
      },
      "source": [
        "## Providing the Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u_S9er6dDA6p"
      },
      "source": [
        "xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)\n",
        "ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fsXKJ6KODA8u"
      },
      "source": [
        "## Training the Neural Network"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BjkGKQngDDM9",
        "outputId": "68e1ca9d-ec27-4549-fc84-cc07e0f25b79"
      },
      "source": [
        "model.fit(xs, ys, epochs=500)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/500\n",
            "1/1 [==============================] - 0s 259ms/step - loss: 32.8893\n",
            "Epoch 2/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 26.2011\n",
            "Epoch 3/500\n",
            "1/1 [==============================] - 0s 7ms/step - loss: 20.9325\n",
            "Epoch 4/500\n",
            "1/1 [==============================] - 0s 15ms/step - loss: 16.7809\n",
            "Epoch 5/500\n",
            "1/1 [==============================] - 0s 7ms/step - loss: 13.5081\n",
            "Epoch 6/500\n",
            "1/1 [==============================] - 0s 8ms/step - loss: 10.9270\n",
            "Epoch 7/500\n",
            "1/1 [==============================] - 0s 7ms/step - loss: 8.8902\n",
            "Epoch 8/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 7.2817\n",
            "Epoch 9/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 6.0103\n",
            "Epoch 10/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 5.0042\n",
            "Epoch 11/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 4.2070\n",
            "Epoch 12/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 3.5743\n",
            "Epoch 13/500\n",
            "1/1 [==============================] - 0s 11ms/step - loss: 3.0711\n",
            "Epoch 14/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 2.6698\n",
            "Epoch 15/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 2.3489\n",
            "Epoch 16/500\n",
            "1/1 [==============================] - 0s 8ms/step - loss: 2.0914\n",
            "Epoch 17/500\n",
            "1/1 [==============================] - 0s 12ms/step - loss: 1.8837\n",
            "Epoch 18/500\n",
            "1/1 [==============================] - 0s 3ms/step - loss: 1.7155\n",
            "Epoch 19/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.5783\n",
            "Epoch 20/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.4657\n",
            "Epoch 21/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 1.3725\n",
            "Epoch 22/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 1.2947\n",
            "Epoch 23/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.2290\n",
            "Epoch 24/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 1.1731\n",
            "Epoch 25/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.1248\n",
            "Epoch 26/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.0827\n",
            "Epoch 27/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.0455\n",
            "Epoch 28/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 1.0122\n",
            "Epoch 29/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.9822\n",
            "Epoch 30/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.9547\n",
            "Epoch 31/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.9294\n",
            "Epoch 32/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 0.9058\n",
            "Epoch 33/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.8836\n",
            "Epoch 34/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.8627\n",
            "Epoch 35/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.8428\n",
            "Epoch 36/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.8237\n",
            "Epoch 37/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.8054\n",
            "Epoch 38/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.7878\n",
            "Epoch 39/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.7708\n",
            "Epoch 40/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.7543\n",
            "Epoch 41/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.7383\n",
            "Epoch 42/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.7227\n",
            "Epoch 43/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.7076\n",
            "Epoch 44/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6928\n",
            "Epoch 45/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6783\n",
            "Epoch 46/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6642\n",
            "Epoch 47/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6505\n",
            "Epoch 48/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6370\n",
            "Epoch 49/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6239\n",
            "Epoch 50/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.6110\n",
            "Epoch 51/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5984\n",
            "Epoch 52/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5861\n",
            "Epoch 53/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5740\n",
            "Epoch 54/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5622\n",
            "Epoch 55/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5506\n",
            "Epoch 56/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5393\n",
            "Epoch 57/500\n",
            "1/1 [==============================] - 0s 3ms/step - loss: 0.5282\n",
            "Epoch 58/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5173\n",
            "Epoch 59/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.5067\n",
            "Epoch 60/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4963\n",
            "Epoch 61/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4861\n",
            "Epoch 62/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 0.4761\n",
            "Epoch 63/500\n",
            "1/1 [==============================] - 0s 5ms/step - loss: 0.4663\n",
            "Epoch 64/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4567\n",
            "Epoch 65/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4474\n",
            "Epoch 66/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4382\n",
            "Epoch 67/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4292\n",
            "Epoch 68/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 0.4204\n",
            "Epoch 69/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.4117\n",
            "Epoch 70/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 0.4033\n",
            "Epoch 71/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.3950\n",
            "Epoch 72/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 0.3869\n",
            "Epoch 73/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.3789\n",
            "Epoch 74/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.3711\n",
            "Epoch 75/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.3635\n",
            "Epoch 76/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 0.3560\n",
            "Epoch 77/500\n",
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            "Epoch 78/500\n",
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            "1/1 [==============================] - 0s 5ms/step - loss: 7.0294e-05\n",
            "Epoch 488/500\n",
            "1/1 [==============================] - 0s 24ms/step - loss: 6.8850e-05\n",
            "Epoch 489/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 6.7435e-05\n",
            "Epoch 490/500\n",
            "1/1 [==============================] - 0s 17ms/step - loss: 6.6051e-05\n",
            "Epoch 491/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 6.4694e-05\n",
            "Epoch 492/500\n",
            "1/1 [==============================] - 0s 11ms/step - loss: 6.3364e-05\n",
            "Epoch 493/500\n",
            "1/1 [==============================] - 0s 15ms/step - loss: 6.2063e-05\n",
            "Epoch 494/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 6.0789e-05\n",
            "Epoch 495/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 5.9540e-05\n",
            "Epoch 496/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 5.8317e-05\n",
            "Epoch 497/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 5.7118e-05\n",
            "Epoch 498/500\n",
            "1/1 [==============================] - 0s 6ms/step - loss: 5.5946e-05\n",
            "Epoch 499/500\n",
            "1/1 [==============================] - 0s 4ms/step - loss: 5.4796e-05\n",
            "Epoch 500/500\n",
            "1/1 [==============================] - 0s 3ms/step - loss: 5.3671e-05\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tensorflow.python.keras.callbacks.History at 0x7fc739e4cb10>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oW2VHscND8xX",
        "outputId": "8860cde8-cca0-458d-d518-832c77e30a78"
      },
      "source": [
        "print(model.predict([10.0]))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[18.978626]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kkDGuIAyD_1L"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}