{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature :  [1. 0. 0. 1. 0.]  Target :  [0. 1.]\n",
      "Feature :  [1. 1. 0. 0. 1.]  Target :  [1. 0.]\n",
      "Feature :  [1. 1. 1. 0. 1.]  Target :  [1. 0.]\n",
      "Feature :  [1. 1. 0. 1. 1.]  Target :  [1. 0.]\n",
      "Feature :  [0. 0. 1. 1. 1.]  Target :  [0. 1.]\n",
      "Feature :  [0. 0. 0. 1. 1.]  Target :  [0. 1.]\n",
      "Feature :  [1. 1. 1. 1. 1.]  Target :  [1. 0.]\n",
      "Feature :  [0. 0. 0. 0. 0.]  Target :  [0. 1.]\n",
      "Feature :  [1. 0. 1. 1. 0.]  Target :  [0. 1.]\n",
      "Feature :  [1. 0. 1. 1. 1.]  Target :  [1. 0.]\n",
      "Feature :  [1. 0. 0. 0. 0.]  Target :  [0. 1.]\n",
      "Feature :  [0. 1. 0. 1. 1.]  Target :  [0. 1.]\n",
      "Feature :  [0. 0. 0. 0. 1.]  Target :  [0. 1.]\n",
      "Feature :  [1. 1. 1. 1. 0.]  Target :  [0. 1.]\n",
      "Feature :  [1. 0. 0. 0. 1.]  Target :  [1. 0.]\n",
      "Feature :  [0. 1. 1. 1. 1.]  Target :  [0. 1.]\n",
      "Feature :  [1. 1. 0. 0. 0.]  Target :  [0. 1.]\n",
      "Feature :  [1. 0. 0. 1. 1.]  Target :  [1. 0.]\n",
      "Feature :  [1. 1. 0. 1. 0.]  Target :  [0. 1.]\n",
      "Feature :  [1. 1. 1. 0. 0.]  Target :  [0. 1.]\n",
      "Feature :  [0. 0. 1. 0. 1.]  Target :  [0. 1.]\n",
      "Feature :  [1. 0. 1. 0. 1.]  Target :  [1. 0.]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# You should write your target function in this space\n",
    "#====================================================\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "#=====================================================\n",
    "    \n",
    "\n",
    "## Set up training data\n",
    "## Each row is a case\n",
    "## Columns 0-4 are features\n",
    "## Columns 5 & 6 are targets\n",
    "\n",
    "features_and_targets = np.array( \n",
    "                                   [ [0, 0, 0, 0, 0, 0, 1],\n",
    "                                     [0, 0, 0, 0, 1, 0, 1],\n",
    "                                     [0, 0, 0, 1, 1, 0, 1],\n",
    "                                     [0, 0, 1, 1, 1, 0, 1],\n",
    "                                     [0, 1, 1, 1, 1, 0, 1],\n",
    "                                     [1, 1, 1, 1, 0, 0, 1],\n",
    "                                     [1, 1, 1, 0, 0, 0, 1],\n",
    "                                     [1, 1, 0, 0, 0, 0, 1],\n",
    "                                     [1, 0, 0, 0, 0, 0, 1],\n",
    "                                     [1, 0, 0, 1, 0, 0, 1],\n",
    "                                     [1, 0, 1, 1, 0, 0, 1],\n",
    "                                     [1, 1, 0, 1, 0, 0, 1],\n",
    "                                     [0, 1, 0, 1, 1, 0, 1],\n",
    "                                     [0, 0, 1, 0, 1, 0, 1],\n",
    "                                     [1, 0, 1, 1, 1, 1, 0],\n",
    "                                     [1, 1, 0, 1, 1, 1, 0],\n",
    "                                     [1, 0, 1, 0, 1, 1, 0],\n",
    "                                     [1, 0, 0, 0, 1, 1, 0],\n",
    "                                     [1, 1, 0, 0, 1, 1, 0],\n",
    "                                     [1, 1, 1, 0, 1, 1, 0],\n",
    "                                     [1, 1, 1, 1, 1, 1, 0],\n",
    "                                     [1, 0, 0, 1, 1, 1, 0]  ]\n",
    "                           , dtype=float)\n",
    "\n",
    "# shuffle our cases\n",
    "np.random.shuffle(features_and_targets)\n",
    "\n",
    "for i in range(22):\n",
    "    features = features_and_targets[i,0:5]\n",
    "    targets = features_and_targets[i,5:7]\n",
    "    \n",
    "    # Call your target function here based on x\n",
    "    # to compute your target values based on random \n",
    "    # values for all weights and biases then you can add\n",
    "    # your predicted y's to the print statement\n",
    "    \n",
    "    print('Feature : ',features, ' Target : ', targets)\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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