Hello_World_Layers.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/lmoroney/dlaicourse/blob/master/Hello_World_Layers.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "rX8mhOLljYeM"
      },
      "source": [
        "##### Copyright 2019 The TensorFlow Authors."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "cellView": "form",
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        "colab_type": "code",
        "id": "BZSlp3DAjdYf"
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      "outputs": [],
      "source": [
        "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "# you may not use this file except in compliance with the License.\n",
        "# You may obtain a copy of the License at\n",
        "#\n",
        "# https://www.apache.org/licenses/LICENSE-2.0\n",
        "#\n",
        "# Unless required by applicable law or agreed to in writing, software\n",
        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "# See the License for the specific language governing permissions and\n",
        "# limitations under the License."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 0,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "szbFLdZwPRhK"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "from tensorflow import keras\n",
        "\n",
        "layer_0 = keras.layers.Dense(units=1, input_shape=[1])\n",
        "model = tf.keras.Sequential([layer_0])\n",
        "\n",
        "model.compile(optimizer='sgd', loss='mean_squared_error')\n",
        "\n",
        "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)\n",
        "\n",
        "model.fit(xs, ys, epochs=500)\n",
        "\n",
        "print(model.predict([10.0]))\n",
        "\n",
        "print(\"Layer variables look like this: {}\".format(layer_0.get_weights()))\n"
      ]
    }
  ],
  "metadata": {
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      "name": "Hello_World_Layers.ipynb",
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    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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  "nbformat": 4,
  "nbformat_minor": 0
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