diff --git a/Tasks/daily tasks/GopikrishnanK/.ipynb_checkpoints/Day4_Task-checkpoint.ipynb b/Tasks/daily tasks/GopikrishnanK/.ipynb_checkpoints/Day4_Task-checkpoint.ipynb
new file mode 100644
index 0000000..2fd6442
--- /dev/null
+++ b/Tasks/daily tasks/GopikrishnanK/.ipynb_checkpoints/Day4_Task-checkpoint.ipynb	
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Tasks/daily tasks/GopikrishnanK/Day4_Task.ipynb b/Tasks/daily tasks/GopikrishnanK/Day4_Task.ipynb
new file mode 100644
index 0000000..afba5cf
--- /dev/null
+++ b/Tasks/daily tasks/GopikrishnanK/Day4_Task.ipynb	
@@ -0,0 +1,91 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import torch.nn as nn\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class DummyMod(nn.Module):\n",
+    "    def __init__(self,ip_size):\n",
+    "        self.ip = nn.Linear(i,64)\n",
+    "        self.h1 = nn.Linear(64,128)\n",
+    "        self.h2 = nn.Linear(128,32)\n",
+    "        self.op = nn.Linear(32,1)\n",
+    "        self.sigmo = nn.Sigmoid()\n",
+    "        \n",
+    "    def forward(x):\n",
+    "        x = self.ip(x)\n",
+    "        x = self.h1(x)\n",
+    "        x = self.sigmo(x)\n",
+    "        x = self.h2(x)\n",
+    "        x = self.op(x)\n",
+    "        return(x)\n",
+    "    \n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "DummyMod(\n",
+      "  (ip): Linear(in_features=128, out_features=64, bias=True)\n",
+      "  (h1): Linear(in_features=64, out_features=128, bias=True)\n",
+      "  (h2): Linear(in_features=128, out_features=32, bias=True)\n",
+      "  (op): Linear(in_features=32, out_features=1, bias=True)\n",
+      "  (sigmo): Sigmoid()\n",
+      ")\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = DummyMod()\n",
+    "print(model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}