ReLu_Approximation_of_function_Assingment_DL.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ReLu_Approximation_of_function_Assingment_DL.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/souvikg123/SOUVIK/blob/master/ReLu_Approximation_of_function_Assingment_DL.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8_0yeQWvvlMR"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2JOJcI8VxA8n"
      },
      "source": [
        "def reLu(x):\n",
        "  return np.maximum(0,x)"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vhrEWCEExGMh",
        "outputId": "1faab56e-02da-4297-947f-b15c30a8b305"
      },
      "source": [
        "x = np.arange(-2,2,0.2)\n",
        "x"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-2.0000000e+00, -1.8000000e+00, -1.6000000e+00, -1.4000000e+00,\n",
              "       -1.2000000e+00, -1.0000000e+00, -8.0000000e-01, -6.0000000e-01,\n",
              "       -4.0000000e-01, -2.0000000e-01, -4.4408921e-16,  2.0000000e-01,\n",
              "        4.0000000e-01,  6.0000000e-01,  8.0000000e-01,  1.0000000e+00,\n",
              "        1.2000000e+00,  1.4000000e+00,  1.6000000e+00,  1.8000000e+00])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "eQkJeRsjxH6R",
        "outputId": "ef9b3543-4abb-41fa-c923-f0c7ce964606"
      },
      "source": [
        "plt.axhline(0,color='grey')\n",
        "plt.axvline(0,color='grey') \n",
        "plt.plot(x,reLu(x))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9241c4e240>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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umJFD97TGPHj1mWHHqTU0dCMiNcLduXvWUr46fIxpPxpCo3oqPzVFPXoRqRFTP97C+2vzeeCKPpx5WrOw49QqKvQiUu1W5O1l0hurubRPW344rEvYcWodFXoRqVYHj5ZOcdC6cX0eu74/ZprioKZpkExEqtXEV1eydfdBXvyXobRsXC/sOLWSevQiUm1eyc7jpSW5jLu4J0O7tw47Tq2lQi8i1WLr7oM88PJyvtW1JRMu7hF2nFpNhV5EYq6wqITxmdnUTanDE6MGUVdTHIRKY/QiEnP//fZaluXu5dnvn02HFg3DjlPr6WVWRGLqw3X5TFmwie8P7cyIs9qFHUdQoReRGNq5/wg/n5nDGW2b8u9XaoqDeKGhGxGJiZIS5+czl3LgaBEv/stQGqSmhB1JAurRi0hM/O/fNvG39buYeFVferVtGnYciaBCLyJVlrPtKx57ay2Xn9WO0UM6Vb6B1CgVehGpkv1HjjEhM5u2zRow6VpNcRCPoir0ZjbCzNaa2QYzu7ec9t+bWU5wW2dmX0W0FUe0zY1leBEJl7vzwMsryPvqME+NHkjzRqlhR5JyVPphrJmlAM8A3wVygUVmNtfdVx1fx93vjFh/PDAo4ikOu/vA2EUWkXgxe3Euc5d+wd3De3F2l1Zhx5EKRNOjHwJscPdN7l4ITAdGnmD90UBmLMKJSPzamH+Aia+uZGj3VvzkQk1xEM+iKfQdgG0Rj3ODZd9gZl2AbsB7EYsbmFmWmS00s2tOOamIxI2jRcWMfzGbBql1eOKmQaTU0bh8PIv1efSjgNnuXhyxrIu755lZd+A9M1vu7hvLbmhmY4GxAJ07d45xLBGJpUlvrGHV9n383y0ZtGveIOw4UoloevR5QOT5Uh2DZeUZRZlhG3fPC35uAj7g6+P3ketNcfcMd89IT0+PIpaIhOHd1Tv448dbGHNuVy7p0zbsOBKFaAr9IqCnmXUzs3qUFvNvnD1jZr2BlsCnEctamln94H4acB6wquy2IpIYvtx7hLtnLeXM9s2474reYceRKFU6dOPuRWY2DngLSAGmuvtKM3sIyHL340V/FDDd3T1i8z7Ac2ZWQumLyqTIs3VEJHEUlzh3zMjmyLESJt88iPp1NcVBoohqjN7d5wHzyiybWObxr8rZ7hOgXxXyiUic+J8PNrBwUwGPXt+f09ObhB1HToK+GSsilVq8tYDfv7Oeqwecxg1ndww7jpwkFXoROaG9h44xITOHDi0a8pvvnaUpDhKQpikWkQq5O/fOWcaOfUeY/ZNzadpAUxwkIvXoRaRCmX/fxhsrvuTuy85gYKcWYceRU6RCLyLlWrdjP79+bSXf7pnG2G93DzuOVIEKvYh8w5FjxYx7cQlNG9Tl8RsHUEdTHCQ0jdGLyDc8/Poq1u04wJ9+PIQ2TTXFQaJTj15EvubNFdt54bPPGfud7lzQS9ORJAMVehH5h7yvDnPP7GUM6Nicu4efEXYciREVehEBoKi4hJ9lZlPi8NToQdSrq/KQLDRGLyIAPPXuerK27uGJmwbSpXXjsONIDOklW0T4dONuJr+/gesGd+SaQeVeV0gSmAq9SC2352Ahd87IoWvrxjw0sm/YcaQaaOhGpBZzd34xeym7Dx7l5VvOo3F9lYRkpB69SC3250+38s7qndx7eR/O6tA87DhSTVToRWqpVV/s4zfzVnNx7zb8+LyuYceRaqRCL1ILHSosYlzmElo0TOWx6/tr6uEkpwE5kVro13NXsXnXQV649RxaN6kfdhypZurRi9Qyry39ghlZ2/jphadzbo+0sONIDYiq0JvZCDNba2YbzOzectrHmFm+meUEt9si2m4xs/XB7ZZYhheRk7Ot4BD3z1nO4M4tuOPSXmHHkRpS6dCNmaUAzwDfBXKBRWY2191XlVl1hruPK7NtK+BBIANwYHGw7Z6YpBeRqB0rLmF8ZjYYPDlqEKkpekNfW0TzLz0E2ODum9y9EJgOjIzy+S8D5rt7QVDc5wMjTi2qiFTF7+avI2fbV0y6tj+dWjUKO47UoGgKfQdgW8Tj3GBZWdeZ2TIzm21mnU5yW8xsrJllmVlWfn5+FLFEJFofrd/Fsx9uZPSQTlzZv33YcaSGxeq922tAV3fvT2mv/U8n+wTuPsXdM9w9Iz1dc2CLxMquA0e5c2YOPdKbMPEqTXFQG0VT6POAThGPOwbL/sHdd7v70eDh88DZ0W4rItWnpMT5+cyl7D18jMk3D6JhvZSwI0kIoin0i4CeZtbNzOoBo4C5kSuYWeR7wauB1cH9t4DhZtbSzFoCw4NlIlIDpn68mQ/X5fMfV/ahd7tmYceRkFR61o27F5nZOEoLdAow1d1XmtlDQJa7zwUmmNnVQBFQAIwJti0ws4cpfbEAeMjdC6rh9xCRMpbn7uWRN9dwWd+2fH9ol7DjSIii+masu88D5pVZNjHi/n3AfRVsOxWYWoWMInKSDhwtYnzmEtKb1OeR6zTFQW2nKRBEktDEV1bwecEhpo8dRotG9cKOIyHTNyZEksycJbnMyc5jwiU9GdKtVdhxJA6o0Iskkc27DvLvr6xgSLdWjL+4Z9hxJE6o0IskicKiEsZnLqFe3To8OWogKXU0Li+lNEYvkiQefXMNK/L2MeUHZ9O+ecOw40gcUY9eJAm8v3Ynz3+0mR8O68Lwvu3CjiNxRoVeJMHt3HeEu2cupXe7ptx/RZ+w40gc0tCNSAIrKXHunJnDwcIiZtw8lAapmuJAvkmFXiSBPbtgIx9v2M2ka/vRo03TsONInNLQjUiCWvL5Hh5/ex1X9m/PTd/qVPkGUmup0IskoH1HjjEhM5v2zRvw22v7aYoDOSEN3YgkGHfn/jnL2b73CLNuH0azBqlhR5I4px69SIKZmbWN15dt567v9mJw55Zhx5EEoEIvkkA27NzPr+au4rwerfnJBaeHHUcShAq9SII4cqyYcS9m07BeCr+/cSB1NMWBRElj9CIJ4rfzVrPmy/38ccy3aNOsQdhxJIGoRy+SAN5e+SV/+nQrt57fjYt6twk7jiQYFXqROLd972HueWkZZ3Voxj0jzgg7jiSgqAq9mY0ws7VmtsHM7i2n/S4zW2Vmy8zsXTPrEtFWbGY5wW1u2W1FpGLFJc4d03MoLCrhqVGDqF9XUxzIyat0jN7MUoBngO8CucAiM5vr7qsiVssGMtz9kJn9BHgUuCloO+zuA2OcW6RWePq9DXy2uYDHbxhA9/QmYceRBBVNj34IsMHdN7l7ITAdGBm5gru/7+6HgocLgY6xjSlS+yzaUsCT767je4M6cN3Z+i8lpy6aQt8B2BbxODdYVpFbgTciHjcwsywzW2hm11S0kZmNDdbLys/PjyKWSPL66lAhP8vMpnOrRjx8zVlhx5EEF9PTK83s+0AGcEHE4i7unmdm3YH3zGy5u28su627TwGmAGRkZHgsc4kkEnfnly8tI//AUV76ybk0qa+zoKVqounR5wGRU+N1DJZ9jZldCjwAXO3uR48vd/e84Ocm4ANgUBXyiiS9//fZ57y1cgf3XNab/h1bhB1HkkA0hX4R0NPMuplZPWAU8LWzZ8xsEPAcpUV+Z8TylmZWP7ifBpwHRH6IKyIR1ny5j4dfX8UFvdK59fxuYceRJFHpe0J3LzKzccBbQAow1d1XmtlDQJa7zwUeA5oAs4LpUj9396uBPsBzZlZC6YvKpDJn64hI4HBhMeNfzKZZg1T++4YBmuJAYiaqwT93nwfMK7NsYsT9SyvY7hOgX1UCitQWD72+ivU7D/CXW4eQ3rR+2HEkieibsSJxYN7y7WT+/XNuv+B0vt0zPew4kmRU6EVClrvnEPe+tIwBnVrw8+G9wo4jSUiFXiRERcUl/Gx6Du4wedQgUlP0X1JiTyfoioToiXfWs3jrHp4aPYjOrRuFHUeSlLoPIiH5ZOMunvlgAzdmdOTqAaeFHUeSmAq9SAgKDhZy54wcuqU15ldX9w07jiQ5FXqRGubu/GLWUvYcPMbk0YNoVE8jqFK9VOhFatgfP97Cu2t2cv8Vvel7WvOw40gtoEIvUoNW5O1l0htruLRPG245t2vYcaSWUKEXqSEHjxYxITOblo1TefT6AQTThYhUOw0OitSQB+euZPPug7x421BaNa4XdhypRdSjF6kBr+bkMXtxLuMv6sGw01uHHUdqGRV6kWq2dfdBHnh5BRldWjLhkp5hx5FaSIVepBoVFpUwITObOgZPjBpIXU1xICHQGL1INXr87bUszd3L//zzYDq21BQHEg51L0SqyYJ1+Ty3YBM3n9OZy/u1DzuO1GIq9CLVIH//Ue6auZRebZsw8aozw44jtZyGbkRirKTEuWtmDvuPHOPFfzmHBqkpYUeSWk49epEY+9+/beJv63cx8Z/OpFfbpmHHEYmu0JvZCDNba2YbzOzectrrm9mMoP0zM+sa0XZfsHytmV0Wu+gi8SfvcF0ee2stl5/VjpuHdA47jggQRaE3sxTgGeBy4ExgtJmVHXS8Fdjj7j2A3wOPBNueCYwC+gIjgD8EzyeSdI4UG7O/aEbbZg2YdG1/TXEgcSOaMfohwAZ33wRgZtOBkcCqiHVGAr8K7s8GnrbSv/KRwHR3PwpsNrMNwfN9eqId7t69m2nTpp3Er1HquS0tKCrRfy4Jx6FjzTnkdfhesy94eeYLYccR+YdoCn0HYFvE41zgnIrWcfciM9sLtA6WLyyzbYfydmJmY4GxAB06lLtKpdLqFVPsKvQSjiN+hG6pe+ncqGHYUUS+Jm7OunH3KcAUgIyMDB8zZsxJP8fJbyESO6XvQhtyKn+7IlX1ox/9qMK2aD6MzQM6RTzuGCwrdx0zqws0B3ZHua2IiFSjaAr9IqCnmXUzs3qUfrg6t8w6c4FbgvvXA++5uwfLRwVn5XQDegJ/j010ERGJRqVDN8GY+zjgLSAFmOruK83sISDL3ecC/wf8JfiwtYDSFwOC9WZS+sFtEfBv7l5cTb+LiIiUI6oxenefB8wrs2xixP0jwA0VbPsb4DdVyCgiIlWgb8aKiCQ5FXoRkSSnQi8ikuRU6EVEkpyVngUZX8wsH9h6ipunAbtiGCfWlK9qlK9qlK9q4jlfF3dPL68hLgt9VZhZlrtnhJ2jIspXNcpXNcpXNfGeryIauhERSXIq9CIiSS4ZC/2UsANUQvmqRvmqRvmqJt7zlSvpxuhFROTrkrFHLyIiEVToRUSSXMIXejN7zMzWmNkyM3vZzFpUsN4JL3BejfluMLOVZlZiZhWelmVmW8xsuZnlmFlWHOYL6/i1MrP5ZrY++NmygvWKg2OXY2Zlp9GujlwnPB7B1NwzgvbPzKxrdWc6yXxjzCw/4pjdVoPZpprZTjNbUUG7mdlTQfZlZja4prJFme9CM9sbcewmlrdeXHH3hL4Bw4G6wf1HgEfKWScF2Ah0B+oBS4EzayhfH+AM4AMg4wTrbQHSQjh+leYL+fg9Ctwb3L+3vH/foO1ADR6zSo8H8FPg2eD+KGBGnOUbAzxd039vwb6/AwwGVlTQfgXwBmDAUOCzOMt3IfB6GMfuVG8J36N397fdvSh4uJDSq1iV9Y8LnLt7IXD8Auc1kW+1u6+tiX2diijzhXb8gv38Kbj/J+CaGtrviURzPCJzzwYuMbOauqBxmP9elXL3BZRet6IiI4E/e6mFQAsza18z6aLKl3ASvtCX8WNKewJllXeB81O7Ann1ceBtM1scXCg9noR5/Nq6+/bg/pdA2wrWa2BmWWa20Myq+8UgmuPxj3WCjsheoHU15/rGvgMV/XtdFwyNzDazTuW0hyUR/r8OM7OlZvaGmfUNO0xl4ubi4CdiZu8A7cppesDdXw3WeYDSq1i9UJPZgn1Xmi8K57t7npm1Aeab2ZqgZxEv+arNifJFPnB3N7OKzgfuEhy/7sB7Zrbc3TfGOmsSeQ3IdPejZvavlL77uDjkTIliCaV/bwfM7ArgFUovkxq3EqLQu/ulJ2o3szHAVcAlHgyilVGtFymvLF+Uz5EX/NxpZi9T+vY7JoU+BvlCO35mtsPM2rv79uDt+84KnuP48dtkZh8Agygdp64O0RyP4+vkmlldoDmwu5rylFVpPnePzPI8pZ+FxItq/XurKnffF3F/npn9wdzX0a4AAAFQSURBVMzS3D1eJztL/KEbMxsB3ANc7e6HKlgtmguch8bMGptZ0+P3Kf2AudxP/EMS5vGLvPD8LcA33oGYWUszqx/cTwPOo/Q6xdUlmuMRmft64L0KOiGh5Csz5n01sLqGskVjLvDD4OybocDeiOG70JlZu+Oft5jZEErraE29iJ+asD8NruoN2EDpeF5OcDt+psNpwLyI9a4A1lHay3ugBvN9j9IxxqPADuCtsvkoPTtiaXBbGW/5Qj5+rYF3gfXAO0CrYHkG8Hxw/1xgeXD8lgO31kCubxwP4CFKOxwADYBZwd/n34HuNXXMosz32+BvbSnwPtC7BrNlAtuBY8Hf3q3A7cDtQbsBzwTZl3OCs9VCyjcu4tgtBM6tyXynctMUCCIiSS7hh25EROTEVOhFRJKcCr2ISJJToRcRSXIq9CIiSU6FXkQkyanQi4gkuf8PKPWsnwGYFCoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jyo8YVWox8TU"
      },
      "source": [
        "# Approximating x^3 + x^2 -x -1"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JbOA-b0IFzY6",
        "outputId": "c81acb9f-b83e-43b5-b91b-61af283d0ab2"
      },
      "source": [
        "x = np.arange(-2,2,0.01)\n",
        "x"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-2.00000000e+00, -1.99000000e+00, -1.98000000e+00, -1.97000000e+00,\n",
              "       -1.96000000e+00, -1.95000000e+00, -1.94000000e+00, -1.93000000e+00,\n",
              "       -1.92000000e+00, -1.91000000e+00, -1.90000000e+00, -1.89000000e+00,\n",
              "       -1.88000000e+00, -1.87000000e+00, -1.86000000e+00, -1.85000000e+00,\n",
              "       -1.84000000e+00, -1.83000000e+00, -1.82000000e+00, -1.81000000e+00,\n",
              "       -1.80000000e+00, -1.79000000e+00, -1.78000000e+00, -1.77000000e+00,\n",
              "       -1.76000000e+00, -1.75000000e+00, -1.74000000e+00, -1.73000000e+00,\n",
              "       -1.72000000e+00, -1.71000000e+00, -1.70000000e+00, -1.69000000e+00,\n",
              "       -1.68000000e+00, -1.67000000e+00, -1.66000000e+00, -1.65000000e+00,\n",
              "       -1.64000000e+00, -1.63000000e+00, -1.62000000e+00, -1.61000000e+00,\n",
              "       -1.60000000e+00, -1.59000000e+00, -1.58000000e+00, -1.57000000e+00,\n",
              "       -1.56000000e+00, -1.55000000e+00, -1.54000000e+00, -1.53000000e+00,\n",
              "       -1.52000000e+00, -1.51000000e+00, -1.50000000e+00, -1.49000000e+00,\n",
              "       -1.48000000e+00, -1.47000000e+00, -1.46000000e+00, -1.45000000e+00,\n",
              "       -1.44000000e+00, -1.43000000e+00, -1.42000000e+00, -1.41000000e+00,\n",
              "       -1.40000000e+00, -1.39000000e+00, -1.38000000e+00, -1.37000000e+00,\n",
              "       -1.36000000e+00, -1.35000000e+00, -1.34000000e+00, -1.33000000e+00,\n",
              "       -1.32000000e+00, -1.31000000e+00, -1.30000000e+00, -1.29000000e+00,\n",
              "       -1.28000000e+00, -1.27000000e+00, -1.26000000e+00, -1.25000000e+00,\n",
              "       -1.24000000e+00, -1.23000000e+00, -1.22000000e+00, -1.21000000e+00,\n",
              "       -1.20000000e+00, -1.19000000e+00, -1.18000000e+00, -1.17000000e+00,\n",
              "       -1.16000000e+00, -1.15000000e+00, -1.14000000e+00, -1.13000000e+00,\n",
              "       -1.12000000e+00, -1.11000000e+00, -1.10000000e+00, -1.09000000e+00,\n",
              "       -1.08000000e+00, -1.07000000e+00, -1.06000000e+00, -1.05000000e+00,\n",
              "       -1.04000000e+00, -1.03000000e+00, -1.02000000e+00, -1.01000000e+00,\n",
              "       -1.00000000e+00, -9.90000000e-01, -9.80000000e-01, -9.70000000e-01,\n",
              "       -9.60000000e-01, -9.50000000e-01, -9.40000000e-01, -9.30000000e-01,\n",
              "       -9.20000000e-01, -9.10000000e-01, -9.00000000e-01, -8.90000000e-01,\n",
              "       -8.80000000e-01, -8.70000000e-01, -8.60000000e-01, -8.50000000e-01,\n",
              "       -8.40000000e-01, -8.30000000e-01, -8.20000000e-01, -8.10000000e-01,\n",
              "       -8.00000000e-01, -7.90000000e-01, -7.80000000e-01, -7.70000000e-01,\n",
              "       -7.60000000e-01, -7.50000000e-01, -7.40000000e-01, -7.30000000e-01,\n",
              "       -7.20000000e-01, -7.10000000e-01, -7.00000000e-01, -6.90000000e-01,\n",
              "       -6.80000000e-01, -6.70000000e-01, -6.60000000e-01, -6.50000000e-01,\n",
              "       -6.40000000e-01, -6.30000000e-01, -6.20000000e-01, -6.10000000e-01,\n",
              "       -6.00000000e-01, -5.90000000e-01, -5.80000000e-01, -5.70000000e-01,\n",
              "       -5.60000000e-01, -5.50000000e-01, -5.40000000e-01, -5.30000000e-01,\n",
              "       -5.20000000e-01, -5.10000000e-01, -5.00000000e-01, -4.90000000e-01,\n",
              "       -4.80000000e-01, -4.70000000e-01, -4.60000000e-01, -4.50000000e-01,\n",
              "       -4.40000000e-01, -4.30000000e-01, -4.20000000e-01, -4.10000000e-01,\n",
              "       -4.00000000e-01, -3.90000000e-01, -3.80000000e-01, -3.70000000e-01,\n",
              "       -3.60000000e-01, -3.50000000e-01, -3.40000000e-01, -3.30000000e-01,\n",
              "       -3.20000000e-01, -3.10000000e-01, -3.00000000e-01, -2.90000000e-01,\n",
              "       -2.80000000e-01, -2.70000000e-01, -2.60000000e-01, -2.50000000e-01,\n",
              "       -2.40000000e-01, -2.30000000e-01, -2.20000000e-01, -2.10000000e-01,\n",
              "       -2.00000000e-01, -1.90000000e-01, -1.80000000e-01, -1.70000000e-01,\n",
              "       -1.60000000e-01, -1.50000000e-01, -1.40000000e-01, -1.30000000e-01,\n",
              "       -1.20000000e-01, -1.10000000e-01, -1.00000000e-01, -9.00000000e-02,\n",
              "       -8.00000000e-02, -7.00000000e-02, -6.00000000e-02, -5.00000000e-02,\n",
              "       -4.00000000e-02, -3.00000000e-02, -2.00000000e-02, -1.00000000e-02,\n",
              "        1.77635684e-15,  1.00000000e-02,  2.00000000e-02,  3.00000000e-02,\n",
              "        4.00000000e-02,  5.00000000e-02,  6.00000000e-02,  7.00000000e-02,\n",
              "        8.00000000e-02,  9.00000000e-02,  1.00000000e-01,  1.10000000e-01,\n",
              "        1.20000000e-01,  1.30000000e-01,  1.40000000e-01,  1.50000000e-01,\n",
              "        1.60000000e-01,  1.70000000e-01,  1.80000000e-01,  1.90000000e-01,\n",
              "        2.00000000e-01,  2.10000000e-01,  2.20000000e-01,  2.30000000e-01,\n",
              "        2.40000000e-01,  2.50000000e-01,  2.60000000e-01,  2.70000000e-01,\n",
              "        2.80000000e-01,  2.90000000e-01,  3.00000000e-01,  3.10000000e-01,\n",
              "        3.20000000e-01,  3.30000000e-01,  3.40000000e-01,  3.50000000e-01,\n",
              "        3.60000000e-01,  3.70000000e-01,  3.80000000e-01,  3.90000000e-01,\n",
              "        4.00000000e-01,  4.10000000e-01,  4.20000000e-01,  4.30000000e-01,\n",
              "        4.40000000e-01,  4.50000000e-01,  4.60000000e-01,  4.70000000e-01,\n",
              "        4.80000000e-01,  4.90000000e-01,  5.00000000e-01,  5.10000000e-01,\n",
              "        5.20000000e-01,  5.30000000e-01,  5.40000000e-01,  5.50000000e-01,\n",
              "        5.60000000e-01,  5.70000000e-01,  5.80000000e-01,  5.90000000e-01,\n",
              "        6.00000000e-01,  6.10000000e-01,  6.20000000e-01,  6.30000000e-01,\n",
              "        6.40000000e-01,  6.50000000e-01,  6.60000000e-01,  6.70000000e-01,\n",
              "        6.80000000e-01,  6.90000000e-01,  7.00000000e-01,  7.10000000e-01,\n",
              "        7.20000000e-01,  7.30000000e-01,  7.40000000e-01,  7.50000000e-01,\n",
              "        7.60000000e-01,  7.70000000e-01,  7.80000000e-01,  7.90000000e-01,\n",
              "        8.00000000e-01,  8.10000000e-01,  8.20000000e-01,  8.30000000e-01,\n",
              "        8.40000000e-01,  8.50000000e-01,  8.60000000e-01,  8.70000000e-01,\n",
              "        8.80000000e-01,  8.90000000e-01,  9.00000000e-01,  9.10000000e-01,\n",
              "        9.20000000e-01,  9.30000000e-01,  9.40000000e-01,  9.50000000e-01,\n",
              "        9.60000000e-01,  9.70000000e-01,  9.80000000e-01,  9.90000000e-01,\n",
              "        1.00000000e+00,  1.01000000e+00,  1.02000000e+00,  1.03000000e+00,\n",
              "        1.04000000e+00,  1.05000000e+00,  1.06000000e+00,  1.07000000e+00,\n",
              "        1.08000000e+00,  1.09000000e+00,  1.10000000e+00,  1.11000000e+00,\n",
              "        1.12000000e+00,  1.13000000e+00,  1.14000000e+00,  1.15000000e+00,\n",
              "        1.16000000e+00,  1.17000000e+00,  1.18000000e+00,  1.19000000e+00,\n",
              "        1.20000000e+00,  1.21000000e+00,  1.22000000e+00,  1.23000000e+00,\n",
              "        1.24000000e+00,  1.25000000e+00,  1.26000000e+00,  1.27000000e+00,\n",
              "        1.28000000e+00,  1.29000000e+00,  1.30000000e+00,  1.31000000e+00,\n",
              "        1.32000000e+00,  1.33000000e+00,  1.34000000e+00,  1.35000000e+00,\n",
              "        1.36000000e+00,  1.37000000e+00,  1.38000000e+00,  1.39000000e+00,\n",
              "        1.40000000e+00,  1.41000000e+00,  1.42000000e+00,  1.43000000e+00,\n",
              "        1.44000000e+00,  1.45000000e+00,  1.46000000e+00,  1.47000000e+00,\n",
              "        1.48000000e+00,  1.49000000e+00,  1.50000000e+00,  1.51000000e+00,\n",
              "        1.52000000e+00,  1.53000000e+00,  1.54000000e+00,  1.55000000e+00,\n",
              "        1.56000000e+00,  1.57000000e+00,  1.58000000e+00,  1.59000000e+00,\n",
              "        1.60000000e+00,  1.61000000e+00,  1.62000000e+00,  1.63000000e+00,\n",
              "        1.64000000e+00,  1.65000000e+00,  1.66000000e+00,  1.67000000e+00,\n",
              "        1.68000000e+00,  1.69000000e+00,  1.70000000e+00,  1.71000000e+00,\n",
              "        1.72000000e+00,  1.73000000e+00,  1.74000000e+00,  1.75000000e+00,\n",
              "        1.76000000e+00,  1.77000000e+00,  1.78000000e+00,  1.79000000e+00,\n",
              "        1.80000000e+00,  1.81000000e+00,  1.82000000e+00,  1.83000000e+00,\n",
              "        1.84000000e+00,  1.85000000e+00,  1.86000000e+00,  1.87000000e+00,\n",
              "        1.88000000e+00,  1.89000000e+00,  1.90000000e+00,  1.91000000e+00,\n",
              "        1.92000000e+00,  1.93000000e+00,  1.94000000e+00,  1.95000000e+00,\n",
              "        1.96000000e+00,  1.97000000e+00,  1.98000000e+00,  1.99000000e+00])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JKotPf4cMIkE"
      },
      "source": [
        "f=x**3+x**2-x-1"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "dUHfUdToMUHu",
        "outputId": "770b64db-d8be-4804-a57d-4aeec301e338"
      },
      "source": [
        "plt.plot(x,f)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238e80c88>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "u9EJqnXeMVRk",
        "outputId": "1efc784d-ea9b-4e98-c5c8-a73a0ae5b6f7"
      },
      "source": [
        "f1=reLu(-5*x-7.7)\n",
        "plt.plot(x,f)\n",
        "plt.plot(x,f1)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238dfc940>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oOZ7HzByPWF6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "4e929266-e733-4e71-c4b8-19f0a805c3bb"
      },
      "source": [
        "f2=reLu(-1.2*x-1.3)\n",
        "plt.plot(x,f)\n",
        "plt.plot(x,f2)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238df0c50>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BVht7DinPb8i",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "d908df05-068e-444b-e3ce-54dc7d983745"
      },
      "source": [
        "f3=reLu(1.2*x+1)\n",
        "plt.plot(x,f)\n",
        "plt.plot(x,f3)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238d53940>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "58irQhcQPh3l",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "3056938e-906e-46d1-c78c-89985da4bf0e"
      },
      "source": [
        "f4=reLu(1.2*x-2)\n",
        "plt.plot(x,f)\n",
        "plt.plot(x,f4)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238cc3400>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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OV3/7IY2tHTz8lXwyBuhuP17RwU4Ribi2jgB/98Q6ig8e5dGvzuXs4Wl+l9SjKMhFJKKcc3z3uSJWFR/ip9fP4IIJmX6X1ONoakVEIurfX9/JsnXlfPPyiVw3J9fvcnokBbmIRMx/r9jN/W8Xc8M5I7njsvF+l9NjKchFJCIeW72He1/bzuKZOfzoWt08mfoK2PAUNB32vGnNkYuI5/5QUMYPXtzCFZOH8tPrZ5CY0AtDvPkI7FkFJSug5B2o2RV8/vrHYMo1nnalIBcRTz2/vpzvLNvERROz+M8bZ/WeteLtzbBvTTC0S9+Byo3gAtAnFUbPhzlfgTELYOhUz7tWkIuIZ36/dh93/7GI88Zm8OCX55CclOh3SZHT2QEV66F0RTC8yz6AzlZISILcc2DBt4PBPWIOJEX2gmAKchHxxMPvlvDDl7dx6VnZ/OpLs0np08NC3Dmo3v7xVMne96C1Pvja0Gkw929g7MUw6jxIHhDV0jwJcjO7EvgPIBF42Dn3Yy/aFZHY55zjP98q5mdv7GThtOH8/Asz6ZvUQ6ZTavd9PFVSuhKOHgg+P3gMTP3L4Ih7zEWQ6u/a+LCD3MwSgf8C/gIoBz40sxedc1vDbVtEYltHZ4B7/mcrv3t/L0tm53LvkmkkxfOceGMN7FkZDO+SFXCkNPh8alYwtMcuCH4ePNrXMo/nxYh8LlDsnCsBMLOngcWA90H+1g9h49Pd//fOeVBEmG2EWYMDOgMBOgOOQMDR6RwB5wi44Mjo2OfjqzXAMMzAcJgZCQYJZiQkBB8nfvTY+PQ1Bv7uB9Xgfw0OaGnr5FudAf4pNYGUkgTsvnDqCOPfetMAtDYE2+k7EPLOh3NvCwZ39tkQw8snvQjyEUBZl6/LgXOP38jMbgVuBRg1alT3esoYH3wbExYPfhhhN3F6DbQHHDVHWznc2EZdczt1ze3Ut3QQCDhclzb6JiWQnJRA36QE+iQlkBgK6GNhDdDpHJ2Bjz9aOx2t7Z20dQY+8f84KSGB1OREUpOTSEvpw6B+oY/+fejTdRmZJ7/YYbahGnypoamtgze3HeRwWxvzxmZw1rCBPWM/9B8SDO6c2ZAYP4cQo1apc+4h4CGA/Pz87v3pnHFD8KOHamztYPXuGt7dVU3BniNsr6onENpTI9L7MSlnIBOHDmRsViq56f3ISe/H8PSUsFYGdHQGqG1up7qhlf1Hmik/0sTu0Od9h5spqTpKa0fgo+1HpPfj7OEDmZ6bzvTcQczITWdwqm7R1ZtsKKvlb58opL65nftvms1Zk7L9LqnX8yLI9wNdb/GRG3pOTkNVXQuvFFXy9o6DrC05TFtngP59E5k1Kp2vXTqB/NGDmTkqnbSUPhHpPykxgcwByWQOSD7hFek6A46yw03sPNDAroNH2VHVwJaKOv60/eBHI/lRQ/ozPXcQM0emc+6YDCbnpPXOE0B6OOccv/9gH/e8uJXstGT+cPt5TMkZ5HdZgjdB/iEwwczGEAzwG4AbPWi3x6prbue1zZX8cX0F75fW4ByMzx7AV+aP5pJJ2eTnDYmZo/6JCUZeZip5malcMeXj5xta2inaX8em8jo2ltWyfl8tL22qBGBAchL5eYOZO2YI544ZwrQR6THz/Uj3tLR38s9/3MzSwnIWTMziF1+YqXdiMSTsIHfOdZjZ14DlBJcfPuKc2xJ2ZT3Q5v11PL5mDy9sqKC1I0BeRn/uuHQCV8/MYVxWdNedhmtgSh/mj8tk/riPl11V1jXzQenhjz5+smMHACl9EpgzejAXTsjigvGZTB6eRoJG7HFjR1UDdz69nu1VDdx52QTuuGyC3nHFGHOeHDU/M/n5+a6goCDq/fqhM+B4paiS375Xyrp9tfTrk8g1s0bwhXNGMiN3UI++kFDN0VY+3HOEtaU1rNldw/aqBgAyUvty/vhMLpyQyYUTshg2KMXnSuVEAgHHI++V8pPlO0hLSeK+62ZwyVmaD/eTmRU65/I/8byCPDI6OgO8uLGC+98upqS6kTGZqXx53mium5PLoH6Rme+OdQfrW1hVfIh3dwU/Dh1tBWBC9gAumJDJgolZzBub0fPOCIxDFbXN/OPSjbxXXMPlZ2fz4yXTydSt2XynII+SQMDxwsb9/OLNXeytaeKsYQO547IJXDllmKYTunDOsb2qgVW7DrFyVzUflB6mtSNA36QEzh0zhAUTs1gwMYvx2QN69LuWWNPRGeCxNXv52es7cMD3F03mC+eM1M8gRijIo+CD0sP88OWtbCqvY0pOGndeNoHLzx6qAD8NLe2drC09zMqd1byzs5rig0cByBmUwoJJwVCfPz4zYqt3JLis8O7ni9hSUc/Fk7L418VTGTmkv99lSRcK8ggqO9zE/39lG69urmJYWgp3XTmJa2aOUICHYX9tczDUd1TzXvEhGlo7SEwwZo9KD43Ws5mSo4OmXqiqa+Hnb+zkD4VlZA9M5gefm8Jnpw7TKDwGKcgjoDPgeHT1Hn66PLg64/YF47j1orH066s5Xi+1dwZYv6/2o9F60f46IHjQ9MIJmSyYlMWFE7I0h3uG6lvaeWDFbh55r5RAAP7qvNHcefkEBupdT8xSkHtse1U9315WxMayWi6elMUPr5lK7mC9DY2GQ0dbeXdXNSt3HmLlzmpqGtsAmDoi7aPR+qxR6b3nhgZnqK6pnd+9v4ffrCrlSFM718zM4VtXTNI0ShxQkHukM+B4cOVufvb6TtL69eEHn5vM1TNy9DbUJ4GAY0tFPSt3BadhCvcdoTPgGJicxPzxGSyYmM1FEzP1R5bgqqHfrCrlybX7ONrawSWTsvjWFZOYOkJnZ8YLBbkHqupa+OYzG1hTUsPCacP512umMkRnt8WU+pZ2VhfX8M7OalburGZ/bTMA47JSWTAxmwWTsjh3zJBes8TROceakhp+v3Yfy7dU0RlwLJqew+0LxjE555OXZJDYpiAP0+tbqrhr2SZa2wPcc/UUrs/P1Sg8xjnn2F19lBU7qlm56xDvl9TQ1hEgOSmBc8dmcNGETM7JG8LknLQeNw1TfqSJlzdV8syHZZQcaiQtJYklc3K5eX4eozNS/S5PuklB3k2dAcd9y3fwwDu7mToijf+4YVbcnU4vQc1tnawtrWHlzkO8s/Mgu6sbgeAlBGbkppOfN5j80UOYNSqd9P7x906r7HATy7dU8XJRJev31QIwZ/Rgbpw7ioXTh/eadyE9mYK8G+qa2vn60+tZubOaL84dxf+7enLPvplsL1NV10LB3sMU7j1C4d4jbKmopzN03eBxWalMyRnElJw0JuekMSVnUMxNo9U1tfPhnsOs3FXNu7sOUXoo+Idp6og0Fk7LYeG04YzK0LGBnkRBfoZ2VDVw6+8KqKht5p6rp3Ljud28GYbEjaa2DjaW1VG49zAbymrZWlFPRV3LR68PS0thck4aY0NXgxybmcqYrFSGDkyJ6Hp25xw1jW0UHzzKzgMNbNhXy4ayWkpCwd2vTyLnjcvgwgmZXDIpm7xMTZ30VCcL8vi5BUYUrdp1iNufKKRf30SevnUec0YP8bskiYL+fZM4b1wG543L+Oi5I41tbK2sZ0tFHVsr6tle1cDq3Ydoaf/4ZhspfRLIGdSP7LRkhqalMDQtheyByWQM6Etq3yQGpCQxIDmJ1OQkEkPHVYK33DM6AgEaWztpaG2nsbWTxtYOqhtaqaxr4UB9CxV1zZRUN1LX3P5Rf5kDkpk5Mp0lc3KZPWows0en651iL6cgP87z68v5x2c3MS5rAI/ecg7DB/XzuyTx0eDQlRrPH//x5XoDAUdVfQulhxo/+qiqb+FgfQvr99VyoL7lz+6q1B39+yYyLPRHYeH04YzPGsC47AFMyB7A8EEpOtAuf0ZBHuKc44F3Srj3te3MGzuEB2/K77VXKZRTS0gwckK32usa8Mc456hrbudIUzuNrR00tHTQ2NpBY1sHAedw7uP7HScmGKnJSaQmJzIwuQ+pyYlkDEgmLSVJYS2nTUFO8D/ev7y0ld++t4dF04fz75+fobeq0m1mRnr/vnG58kXiU68P8kDA8b0XNvPk2n3cPD+P7y+arAsxiUhc6dVBHgg4/un5Ip7+sIzbFozlO1eepbezIhJ3em2QdwYcdy3dxLJ15Xz90vH8/V9MVIiLSFzqlUEeCDi+vSwY4t+8fCJ3Xj7B75JERLqtZ11g4jQ45/jhy9tYWljOHZdNUIiLSNzrdUH+yz8V88h7pdw8P49vKsRFpAfoVUH+2/dK+fmbO1kyO5fvL5qsOXER6RF6TZC/uLGCe/5nK1dMHsq9S6ZpiaGI9BhhBbmZ3Wdm281sk5k9b2bpXhXmpcK9h/mHZzcyN28Iv/ziLJJ62LWnRaR3CzfR3gCmOuemAzuB74Zfkrf21jTyN48XkjMohQdvmqNrMotIjxNWkDvnXnfOdYS+fB/IDb8k79Q1tfPVRz8k4ByP3HwOg2PsetIiIl7wco7hFuDVk71oZreaWYGZFVRXV3vY7Ym1dwa4/YlCyg438eCX5zBWd/URkR7qU08IMrM3gWEneOlu59wLoW3uBjqAJ0/WjnPuIeAhCN5YolvVnoEfvbyNNSU1/Pv1Mzh3bMan/wMRkTj1qUHunLv8VK+b2c3AIuAy58fthk7g+fXlPLp6D7ecP4Ylc2JqtkdExHNhnaJvZlcCdwELnHNN3pQUnq0V9Xz3uSLmjhnCd686y+9yREQiLtw58vuBgcAbZrbBzB7woKZuq21q47YnChjUrw//deNs+miZoYj0AmGNyJ1z470qJFyBgOMbz2ygqq6FZ247j6yByX6XJCISFT1myPrrd0tYsaOa739uCrNHDfa7HBGRqOkRQb6hrJb7lu/gs1OH8eVzR/ldjohIVMV9kDe0tHPHU+sZmpbCj/9yui6EJSK9TlzfWMI5x93Pb2Z/bTPP3DqPQf1113sR6X3iekT+bGE5L26s4BuXTSA/b4jf5YiI+CJug7zscBP3vLiFeWOH8HeXxMziGRGRqIvLIA8EHP/w7EbMjJ9eP4NEXVtcRHqxuAzyx9bsYW3pYb636GxyB/f3uxwREV/FXZCXVB/l3te2c8mkLD6fP9LvckREfBdXQd4ZmlJJTkrkx0u01FBEBOJs+eGv3y1h3b5afvGFmQxNS/G7HBGRmBBXI/KhaclcPyeXxTNz/C5FRCRmxNWI/NpZuVw7S9cXFxHpKq5G5CIi8kkKchGROKcgFxGJcwpyEZE4pyAXEYlzCnIRkTinIBcRiXMKchGROGfOueh3alYN7O3mP88EDnlYjldU15mL1dpU15lRXWcmnLpGO+eyjn/SlyAPh5kVOOfy/a7jeKrrzMVqbarrzKiuMxOJujS1IiIS5xTkIiJxLh6D/CG/CzgJ1XXmYrU21XVmVNeZ8byuuJsjFxGRPxePI3IREelCQS4iEudiPsjN7D4z225mm8zseTNLP8l2V5rZDjMrNrPvRKGu681si5kFzOykS4nMbI+ZFZnZBjMriKG6orq/Qn0OMbM3zGxX6PPgk2zXGdpfG8zsxQjVcsrv38ySzeyZ0OtrzSwvEnV0s7abzay6yz76P1Go6REzO2hmm0/yupnZL0M1bzKz2ZGu6TTrutjM6rrsq+9Hqa6RZva2mW0N/X+88wTbeLfPnHMx/QFcASSFHt8L3HuCbRKB3cBYoC+wEZgc4brOBiYBK4D8U2y3B8iM4v761Lr82F+hfn8CfCf0+Dsn+lmGXjsa4To+9fsH/g54IPT4BuCZKP38Tqe2m4H7o/U7FerzImA2sPkkr18FvAoYMA9YGyN1XQy8FM19Fep3ODA79HggsPMEP0fP9lnMj8idc6875zpCX74PnOheb3OBYudciXOuDXgaWBzhurY553ZEso/uOM26or6/QhYDj4UePwZcE4U+T+R0vv+utS4FLjMzi5Haos45txI4fIpNFgOPu6D3gXQzGx4DdfnCOVfpnFsXetwAbANGHLeZZ/ss5oP8OLcQ/At2vBFAWZevy/nkTvOLA143s0Izu9XvYkL82l9DnXOVocdVwNCTbJdiZgVm9r6ZRSLsT+f7/2ib0ECiDsiIQC3dqQ1gSejt+FIzGxmFuj5NLP8fPM/MNprZq2Y2Jdqdh6blZgFrj/hljnwAAAJ/SURBVHvJs30WEzdfNrM3gWEneOlu59wLoW3uBjqAJ2OprtNwgXNuv5llA2+Y2fbQKMLvuiLiVLV1/cI558zsZGtfR4f22VjgLTMrcs7t9rrWOPY/wFPOuVYzu43gO4dLfa4pVq0j+Pt01MyuAv4ITIhW52Y2AFgGfMM5Vx+pfmIiyJ1zl5/qdTO7GVgEXOZCk0vH2Q90HZXkhp6LaF2n2cb+0OeDZvY8wbfOYQW5B3VFZH/BqWszswNmNtw5Vxl6C3nwJG0c22clZraC4GjGyyA/ne//2DblZpYEDAJqPKyh27U557rW8TDBYw9+i9jvVDi6hqdz7hUz+5WZZTrnIn4xLTPrQzDEn3TOPXeCTTzbZzE/tWJmVwJ3AVc755pOstmHwAQzG2NmfQkenIrIaoczYWapZjbw2GOCB25PeHQ9yvzaXy8CXwk9/grwiXcPZjbYzJJDjzOB84GtHtdxOt9/11qvA946ySDCa59a23HzqFcTnH/124vAX4VWYswD6rpMo/nGzIYdO7ZhZnMJZl7E/yCH+vwNsM0597OTbObdPov20dxuHP0tJjiPtCH0cWwlQQ7wynFHgHcSHLndHYW6riU4p9UKHACWH18XwZUHG0MfW2KlLj/2V6jPDOBPwC7gTWBI6Pl84OHQ4/lAUWifFQF/HaFaPvH9A/9CcMAAkAI8G/r9+wAYG419dJq1/Vvo92kj8DZwVhRqegqoBNpDv19/DdwO3B563YD/CtVcxClWckW5rq912VfvA/OjVNcFBI+PbeqSXVdFap/pFH0RkTgX81MrIiJyagpyEZE4pyAXEYlzCnIRkTinIBcRiXMKchGROKcgFxGJc/8L18Zr8kvOOR8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yhFVUvp7PkcW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "e041454a-ae22-4699-e174-d121f46b9cce"
      },
      "source": [
        "f5=reLu(2*x-1.1)\n",
        "plt.plot(x,f)\n",
        "plt.plot(x,f5)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238d02438>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tnKpEHdlPnjp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "1acee86b-26a0-4efc-e496-0cfcee4c1530"
      },
      "source": [
        "f6=reLu(5*x-5)\n",
        "plt.plot(x,f)\n",
        "plt.plot(x,f6)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238c3de48>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MHj4j72MPqVl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "outputId": "8a3e91f2-7ab1-4771-ea00-339cbf274502"
      },
      "source": [
        "plt.axhline(0,color='grey')\n",
        "plt.axvline(0,color='grey') \n",
        "plt.plot(x,f)\n",
        "plt.plot(x,-f1-f2-f3+f4+f5+f6)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f9238ae9c18>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}