diff --git a/SUBMISSION/NaveenPaudel.md b/SUBMISSION/NaveenPaudel.md
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+# Name: Naveen Paudel  
+## Enrollment number: 19608441P
diff --git a/annpractisepart3.ipynb b/annpractisepart3.ipynb
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+++ b/annpractisepart3.ipynb
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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyPDycAexK6flJEfam5CEsKV",
+      "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/NipoTechCRATManiac/Hacktoberfest-2021/blob/main/annpractisepart3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1.Creating Neural Network with Activation Functions\n"
+      ],
+      "metadata": {
+        "id": "XzP77dCNMqoC"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#Creating Input Layer\n",
+        "import numpy as np\n",
+        "data = [5,9]\n",
+        "x0 = data[0]\n",
+        "x1 = data[1]\n",
+        "input_layer = np.array([x0,x1])\n",
+        "print(\"Input Layer \",input_layer)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "AQclHTWqMwUa",
+        "outputId": "a9911719-19e8-4254-cbc3-051c09ccd125"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Input Layer  [5 9]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#Activation Function - Relu\n",
+        "def relu(x):\n",
+        "  return (max(0,x))"
+      ],
+      "metadata": {
+        "id": "ixawUto9Ry2h"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#Activation Function - Sigmoid\n",
+        "def sig(x):\n",
+        "  if x<=0:\n",
+        "    return 0\n",
+        "  else:\n",
+        "    return 1"
+      ],
+      "metadata": {
+        "id": "fA76NFojSASK"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#Creating Hidden Layer1\n",
+        "weights = {'x2':np.array([1, 3]), 'x3':np.array([3,4])}\n",
+        "x2 = (input_layer*weights['x2']).sum()\n",
+        "x3 = (input_layer*weights['x3']).sum()\n",
+        "x2 = relu(x2)\n",
+        "x3 = relu(x3)\n",
+        "hidden_layer1 = np.array([x2,x3])\n",
+        "print(\"Hidden Layer \",hidden_layer1)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "_voCW704Nius",
+        "outputId": "fd57b55b-976b-43a2-de04-54b7c330b69e"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Hidden Layer  [32 51]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#Creating Hidden Layer2\n",
+        "weights = {'x4':np.array([-1, 2]), 'x5':np.array([-2,1])}\n",
+        "x4 = (hidden_layer1*weights['x4']).sum()\n",
+        "x5 = (hidden_layer1*weights['x5']).sum()\n",
+        "x4 = relu(x4)\n",
+        "x5 = relu(x5)\n",
+        "hidden_layer2 = np.array([x4,x5])\n",
+        "print(\"Hidden Layer \",hidden_layer2)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "NvY0nQ0eTEzn",
+        "outputId": "26938712-0d9e-4798-84c3-c985eeb0e52e"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Hidden Layer  [70  0]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#Creating Output Layer\n",
+        "weights = {'x6':np.array([1,-1])}\n",
+        "x6 = (hidden_layer2*weights['x6']).sum()\n",
+        "x6 = sig(x6)\n",
+        "output_layer = np.array([x6])\n",
+        "print(\"Output Layer \",output_layer)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "3WsNw790To4a",
+        "outputId": "58643160-f4da-4d72-e693-f7819580c82b"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Output Layer  [1]\n"
+          ]
+        }
+      ]
+    }
+  ]
+}
\ No newline at end of file