Day_4_Neural_Networks.ipynb

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  "cells": [
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      "cell_type": "markdown",
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        "<a href=\"https://colab.research.google.com/github/ebrarkiziloglu/ML-Notes-and-Workshops/blob/main/Day_4_Neural_Networks.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "# Neural Networks \n",
        "\n",
        "* input layer\n",
        "* hidden layers\n",
        "* output layer\n",
        "\n",
        "![a simple model](https://upload.wikimedia.org/wikipedia/commons/thumb/9/99/Neural_network_example.svg/1200px-Neural_network_example.svg.png)\n",
        "\n",
        "We'll use pytorch module for this implementation."
      ],
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      "source": [
        "from torch.nn.functional import F\n",
        "\n",
        "class MyNeuralNetwork(nn.Module):\n",
        "  def __init__(self):\n",
        "    super().__init__()\n",
        "    self.layer1 = nn.Linear(num_of_input_nodes, num_of_outgoing_nodes)\n",
        "    ...\n",
        "    self.layeri = nn.Linear(num_of_incoming_nodes, num_of_outgoing_nodes)\n",
        "    ...\n",
        "    self.out = nn.Linear(num_of_incoming_nodes, num_of_output_nodes)\n",
        "\n",
        "  def forward(self, x):\n",
        "    x = F.sigmoid(self.layer1(x))\n",
        "    ...\n",
        "    x = F.relu(self.layeri(x))\n",
        "    ...\n",
        "    return F.sigmoid(self.out(x))\n",
        "\n",
        "model = MyNeuralNetwork()\n",
        "print(model)\n"
      ]
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