diff --git a/iris.data b/iris.data
new file mode 100644
index 0000000..396653c
--- /dev/null
+++ b/iris.data
@@ -0,0 +1,150 @@
+5.1,3.5,1.4,0.2,Iris-setosa
+4.9,3.0,1.4,0.2,Iris-setosa
+4.7,3.2,1.3,0.2,Iris-setosa
+4.6,3.1,1.5,0.2,Iris-setosa
+5.0,3.6,1.4,0.2,Iris-setosa
+5.4,3.9,1.7,0.4,Iris-setosa
+4.6,3.4,1.4,0.3,Iris-setosa
+5.0,3.4,1.5,0.2,Iris-setosa
+4.4,2.9,1.4,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+5.4,3.7,1.5,0.2,Iris-setosa
+4.8,3.4,1.6,0.2,Iris-setosa
+4.8,3.0,1.4,0.1,Iris-setosa
+4.3,3.0,1.1,0.1,Iris-setosa
+5.8,4.0,1.2,0.2,Iris-setosa
+5.7,4.4,1.5,0.4,Iris-setosa
+5.4,3.9,1.3,0.4,Iris-setosa
+5.1,3.5,1.4,0.3,Iris-setosa
+5.7,3.8,1.7,0.3,Iris-setosa
+5.1,3.8,1.5,0.3,Iris-setosa
+5.4,3.4,1.7,0.2,Iris-setosa
+5.1,3.7,1.5,0.4,Iris-setosa
+4.6,3.6,1.0,0.2,Iris-setosa
+5.1,3.3,1.7,0.5,Iris-setosa
+4.8,3.4,1.9,0.2,Iris-setosa
+5.0,3.0,1.6,0.2,Iris-setosa
+5.0,3.4,1.6,0.4,Iris-setosa
+5.2,3.5,1.5,0.2,Iris-setosa
+5.2,3.4,1.4,0.2,Iris-setosa
+4.7,3.2,1.6,0.2,Iris-setosa
+4.8,3.1,1.6,0.2,Iris-setosa
+5.4,3.4,1.5,0.4,Iris-setosa
+5.2,4.1,1.5,0.1,Iris-setosa
+5.5,4.2,1.4,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+5.0,3.2,1.2,0.2,Iris-setosa
+5.5,3.5,1.3,0.2,Iris-setosa
+4.9,3.1,1.5,0.1,Iris-setosa
+4.4,3.0,1.3,0.2,Iris-setosa
+5.1,3.4,1.5,0.2,Iris-setosa
+5.0,3.5,1.3,0.3,Iris-setosa
+4.5,2.3,1.3,0.3,Iris-setosa
+4.4,3.2,1.3,0.2,Iris-setosa
+5.0,3.5,1.6,0.6,Iris-setosa
+5.1,3.8,1.9,0.4,Iris-setosa
+4.8,3.0,1.4,0.3,Iris-setosa
+5.1,3.8,1.6,0.2,Iris-setosa
+4.6,3.2,1.4,0.2,Iris-setosa
+5.3,3.7,1.5,0.2,Iris-setosa
+5.0,3.3,1.4,0.2,Iris-setosa
+7.0,3.2,4.7,1.4,Iris-versicolor
+6.4,3.2,4.5,1.5,Iris-versicolor
+6.9,3.1,4.9,1.5,Iris-versicolor
+5.5,2.3,4.0,1.3,Iris-versicolor
+6.5,2.8,4.6,1.5,Iris-versicolor
+5.7,2.8,4.5,1.3,Iris-versicolor
+6.3,3.3,4.7,1.6,Iris-versicolor
+4.9,2.4,3.3,1.0,Iris-versicolor
+6.6,2.9,4.6,1.3,Iris-versicolor
+5.2,2.7,3.9,1.4,Iris-versicolor
+5.0,2.0,3.5,1.0,Iris-versicolor
+5.9,3.0,4.2,1.5,Iris-versicolor
+6.0,2.2,4.0,1.0,Iris-versicolor
+6.1,2.9,4.7,1.4,Iris-versicolor
+5.6,2.9,3.6,1.3,Iris-versicolor
+6.7,3.1,4.4,1.4,Iris-versicolor
+5.6,3.0,4.5,1.5,Iris-versicolor
+5.8,2.7,4.1,1.0,Iris-versicolor
+6.2,2.2,4.5,1.5,Iris-versicolor
+5.6,2.5,3.9,1.1,Iris-versicolor
+5.9,3.2,4.8,1.8,Iris-versicolor
+6.1,2.8,4.0,1.3,Iris-versicolor
+6.3,2.5,4.9,1.5,Iris-versicolor
+6.1,2.8,4.7,1.2,Iris-versicolor
+6.4,2.9,4.3,1.3,Iris-versicolor
+6.6,3.0,4.4,1.4,Iris-versicolor
+6.8,2.8,4.8,1.4,Iris-versicolor
+6.7,3.0,5.0,1.7,Iris-versicolor
+6.0,2.9,4.5,1.5,Iris-versicolor
+5.7,2.6,3.5,1.0,Iris-versicolor
+5.5,2.4,3.8,1.1,Iris-versicolor
+5.5,2.4,3.7,1.0,Iris-versicolor
+5.8,2.7,3.9,1.2,Iris-versicolor
+6.0,2.7,5.1,1.6,Iris-versicolor
+5.4,3.0,4.5,1.5,Iris-versicolor
+6.0,3.4,4.5,1.6,Iris-versicolor
+6.7,3.1,4.7,1.5,Iris-versicolor
+6.3,2.3,4.4,1.3,Iris-versicolor
+5.6,3.0,4.1,1.3,Iris-versicolor
+5.5,2.5,4.0,1.3,Iris-versicolor
+5.5,2.6,4.4,1.2,Iris-versicolor
+6.1,3.0,4.6,1.4,Iris-versicolor
+5.8,2.6,4.0,1.2,Iris-versicolor
+5.0,2.3,3.3,1.0,Iris-versicolor
+5.6,2.7,4.2,1.3,Iris-versicolor
+5.7,3.0,4.2,1.2,Iris-versicolor
+5.7,2.9,4.2,1.3,Iris-versicolor
+6.2,2.9,4.3,1.3,Iris-versicolor
+5.1,2.5,3.0,1.1,Iris-versicolor
+5.7,2.8,4.1,1.3,Iris-versicolor
+6.3,3.3,6.0,2.5,Iris-virginica
+5.8,2.7,5.1,1.9,Iris-virginica
+7.1,3.0,5.9,2.1,Iris-virginica
+6.3,2.9,5.6,1.8,Iris-virginica
+6.5,3.0,5.8,2.2,Iris-virginica
+7.6,3.0,6.6,2.1,Iris-virginica
+4.9,2.5,4.5,1.7,Iris-virginica
+7.3,2.9,6.3,1.8,Iris-virginica
+6.7,2.5,5.8,1.8,Iris-virginica
+7.2,3.6,6.1,2.5,Iris-virginica
+6.5,3.2,5.1,2.0,Iris-virginica
+6.4,2.7,5.3,1.9,Iris-virginica
+6.8,3.0,5.5,2.1,Iris-virginica
+5.7,2.5,5.0,2.0,Iris-virginica
+5.8,2.8,5.1,2.4,Iris-virginica
+6.4,3.2,5.3,2.3,Iris-virginica
+6.5,3.0,5.5,1.8,Iris-virginica
+7.7,3.8,6.7,2.2,Iris-virginica
+7.7,2.6,6.9,2.3,Iris-virginica
+6.0,2.2,5.0,1.5,Iris-virginica
+6.9,3.2,5.7,2.3,Iris-virginica
+5.6,2.8,4.9,2.0,Iris-virginica
+7.7,2.8,6.7,2.0,Iris-virginica
+6.3,2.7,4.9,1.8,Iris-virginica
+6.7,3.3,5.7,2.1,Iris-virginica
+7.2,3.2,6.0,1.8,Iris-virginica
+6.2,2.8,4.8,1.8,Iris-virginica
+6.1,3.0,4.9,1.8,Iris-virginica
+6.4,2.8,5.6,2.1,Iris-virginica
+7.2,3.0,5.8,1.6,Iris-virginica
+7.4,2.8,6.1,1.9,Iris-virginica
+7.9,3.8,6.4,2.0,Iris-virginica
+6.4,2.8,5.6,2.2,Iris-virginica
+6.3,2.8,5.1,1.5,Iris-virginica
+6.1,2.6,5.6,1.4,Iris-virginica
+7.7,3.0,6.1,2.3,Iris-virginica
+6.3,3.4,5.6,2.4,Iris-virginica
+6.4,3.1,5.5,1.8,Iris-virginica
+6.0,3.0,4.8,1.8,Iris-virginica
+6.9,3.1,5.4,2.1,Iris-virginica
+6.7,3.1,5.6,2.4,Iris-virginica
+6.9,3.1,5.1,2.3,Iris-virginica
+5.8,2.7,5.1,1.9,Iris-virginica
+6.8,3.2,5.9,2.3,Iris-virginica
+6.7,3.3,5.7,2.5,Iris-virginica
+6.7,3.0,5.2,2.3,Iris-virginica
+6.3,2.5,5.0,1.9,Iris-virginica
+6.5,3.0,5.2,2.0,Iris-virginica
+6.2,3.4,5.4,2.3,Iris-virginica
+5.9,3.0,5.1,1.8,Iris-virginica
\ No newline at end of file
diff --git a/neuron.ipynb b/neuron.ipynb
new file mode 100644
index 0000000..0f5b1af
--- /dev/null
+++ b/neuron.ipynb
@@ -0,0 +1,378 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import random"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Neuoron:\n",
+    "    def __init__(self,itemName):\n",
+    "        self.itemName=itemName\n",
+    "        self.weightList = []\n",
+    "        self.addWeight()\n",
+    "\n",
+    "    def addWeight(self):\n",
+    "        w1 = random.randint(0,1000)/1000\n",
+    "        w2 = random.randint(0,1000)/1000\n",
+    "        w3 = random.randint(0,1000)/1000\n",
+    "        w4 = random.randint(0,1000)/1000\n",
+    "        self.weightList = [w1, w2, w3, w4]\n",
+    "    \n",
+    "    def printWeight(self):\n",
+    "        print(self.itemName,\"--\",self.weightList)\n",
+    "    \n",
+    "    def calculate(self,inputlist):\n",
+    "        sum=0\n",
+    "        \n",
+    "        for i in range(len(inputlist)):\n",
+    "            sum += float(inputlist[i])*float(self.weightList[i])\n",
+    "        \n",
+    "        return sum\n",
+    "    \n",
+    "    def increaseWeight(self,landa):\n",
+    "        for i in range(len(self.weightList)):\n",
+    "            self.weightList[i] += landa\n",
+    "    \n",
+    "    def decreaseWeight(self,landa):\n",
+    "        for i in range(len(self.weightList)):\n",
+    "            self.weightList[i] -= landa\n",
+    "    \n",
+    "    def getName(self):\n",
+    "        return self.itemName\n",
+    "\n",
+    "\n",
+    "    \n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "unsupported operand type(s) for +: 'float' and 'str'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn [113], line 3\u001b[0m\n\u001b[0;32m      1\u001b[0m a \u001b[39m=\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m0.5\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m      2\u001b[0m b \u001b[39m=\u001b[39m \u001b[39mfloat\u001b[39m(a)\n\u001b[1;32m----> 3\u001b[0m \u001b[39mprint\u001b[39m(b\u001b[39m+\u001b[39;49ma)\n",
+      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'float' and 'str'"
+     ]
+    }
+   ],
+   "source": [
+    "a = \"0.5\"\n",
+    "b = float(a)\n",
+    "print(b+a)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 146,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n",
+    "class NeuralNetwork:\n",
+    "    def __init__(self,N1,N2,N3):\n",
+    "        self.count =0\n",
+    "        self.N1 = N1\n",
+    "        self.N2 = N2\n",
+    "        self.N3 = N3\n",
+    "    \n",
+    "    def train(self,RawDataset,landa,epok):\n",
+    "        for _ in range(epok):\n",
+    "            for i in range(150):\n",
+    "                inputlist =RawDataset[i]\n",
+    "                N1W1 = self.N1.calculate(inputlist[:4])\n",
+    "                N2W2 = self.N2.calculate(inputlist[:4])\n",
+    "                N3W3 = self.N3.calculate(inputlist[:4])\n",
+    "\n",
+    "                maxResult = max([N1W1,N2W2,N3W3])\n",
+    "\n",
+    "                if (maxResult == N1W1):\n",
+    "                    maxW = self.N1\n",
+    "                elif (maxResult == N2W2):\n",
+    "                    maxW = self.N2\n",
+    "                else:\n",
+    "                    maxW = self.N3\n",
+    "\n",
+    "                if maxW.getName() != inputlist[4]:\n",
+    "                    maxW.decreaseWeight(landa)\n",
+    "                    if inputlist[4] == self.N1.getName():\n",
+    "                        self.N1.increaseWeight(landa)\n",
+    "                    elif inputlist[4] == self.N2.getName():\n",
+    "                        self.N2.increaseWeight(landa)\n",
+    "                    else:\n",
+    "                        self.N3.increaseWeight(landa)\n",
+    "                else:\n",
+    "                    self.count += 1\n",
+    "\n",
+    "\n",
+    "    def output(self):\n",
+    "        self.N1.printWeight()\n",
+    "        self.N2.printWeight()\n",
+    "        self.N3.printWeight()\n",
+    "        print(f\"yüzde {(self.count/(150*20))*100} dogru biliyor\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.79, 0.46, 0.45, 0.05]\n"
+     ]
+    }
+   ],
+   "source": [
+    "n1 = Neuoron()\n",
+    "n1.printWeight()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "7.095\n"
+     ]
+    }
+   ],
+   "source": [
+    "n1.calculate([5.1,3.5,1.4,0.2,\"lale\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.8600000000000001, 0.53, 0.52, 0.11999999999999998]\n",
+      "[0.8700000000000001, 0.54, 0.53, 0.12999999999999998]\n"
+     ]
+    }
+   ],
+   "source": [
+    "n1.printWeight()\n",
+    "n1.increaseWeight(0.01)\n",
+    "n1.printWeight()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "n1 = Neuoron(\"lale\")\n",
+    "n2 = Neuoron(\"gül\")\n",
+    "n3 = Neuoron(\"papatya\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "lale -- [0.17, 0.74, 0.47, 0.67]\n",
+      "gül -- [0.21, 0.51, 0.02, 0.56]\n",
+      "papatya -- [0.88, 0.3, 0.8, 0.56]\n",
+      "4.2490000000000006\n",
+      "2.996\n",
+      "6.77\n",
+      "lale -- [0.27, 0.84, 0.57, 0.77]\n",
+      "gül -- [0.21, 0.51, 0.02, 0.56]\n",
+      "papatya -- [0.78, 0.19999999999999998, 0.7000000000000001, 0.4600000000000001]\n"
+     ]
+    }
+   ],
+   "source": [
+    "NeuralNetwork1 = NeuralNetwork(N1=n1,N2=n2,N3=n3)\n",
+    "NeuralNetwork1.output()\n",
+    "NeuralNetwork1.mini_train(input=[5.1, 3.5, 1.4, 0.2,\"lale\"],landa=0.1)\n",
+    "NeuralNetwork1.output()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 180,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[['5.1', '3.5', '1.4', '0.2', 'Iris-setosa'], ['4.9', '3.0', '1.4', '0.2', 'Iris-setosa'], ['4.7', '3.2', '1.3', '0.2', 'Iris-setosa'], ['4.6', '3.1', '1.5', '0.2', 'Iris-setosa'], ['5.0', '3.6', '1.4', '0.2', 'Iris-setosa'], ['5.4', '3.9', '1.7', '0.4', 'Iris-setosa'], ['4.6', '3.4', '1.4', '0.3', 'Iris-setosa'], ['5.0', '3.4', '1.5', '0.2', 'Iris-setosa'], ['4.4', '2.9', '1.4', '0.2', 'Iris-setosa'], ['4.9', '3.1', '1.5', '0.1', 'Iris-setosa'], ['5.4', '3.7', '1.5', '0.2', 'Iris-setosa'], ['4.8', '3.4', '1.6', '0.2', 'Iris-setosa'], ['4.8', '3.0', '1.4', '0.1', 'Iris-setosa'], ['4.3', '3.0', '1.1', '0.1', 'Iris-setosa'], ['5.8', '4.0', '1.2', '0.2', 'Iris-setosa'], ['5.7', '4.4', '1.5', '0.4', 'Iris-setosa'], ['5.4', '3.9', '1.3', '0.4', 'Iris-setosa'], ['5.1', '3.5', '1.4', '0.3', 'Iris-setosa'], ['5.7', '3.8', '1.7', '0.3', 'Iris-setosa'], ['5.1', '3.8', '1.5', '0.3', 'Iris-setosa'], ['5.4', '3.4', '1.7', '0.2', 'Iris-setosa'], ['5.1', '3.7', '1.5', '0.4', 'Iris-setosa'], ['4.6', '3.6', '1.0', '0.2', 'Iris-setosa'], ['5.1', '3.3', '1.7', '0.5', 'Iris-setosa'], ['4.8', '3.4', '1.9', '0.2', 'Iris-setosa'], ['5.0', '3.0', '1.6', '0.2', 'Iris-setosa'], ['5.0', '3.4', '1.6', '0.4', 'Iris-setosa'], ['5.2', '3.5', '1.5', '0.2', 'Iris-setosa'], ['5.2', '3.4', '1.4', '0.2', 'Iris-setosa'], ['4.7', '3.2', '1.6', '0.2', 'Iris-setosa'], ['4.8', '3.1', '1.6', '0.2', 'Iris-setosa'], ['5.4', '3.4', '1.5', '0.4', 'Iris-setosa'], ['5.2', '4.1', '1.5', '0.1', 'Iris-setosa'], ['5.5', '4.2', '1.4', '0.2', 'Iris-setosa'], ['4.9', '3.1', '1.5', '0.1', 'Iris-setosa'], ['5.0', '3.2', '1.2', '0.2', 'Iris-setosa'], ['5.5', '3.5', '1.3', '0.2', 'Iris-setosa'], ['4.9', '3.1', '1.5', '0.1', 'Iris-setosa'], ['4.4', '3.0', '1.3', '0.2', 'Iris-setosa'], ['5.1', '3.4', '1.5', '0.2', 'Iris-setosa'], ['5.0', '3.5', '1.3', '0.3', 'Iris-setosa'], ['4.5', '2.3', '1.3', '0.3', 'Iris-setosa'], ['4.4', '3.2', '1.3', '0.2', 'Iris-setosa'], ['5.0', '3.5', '1.6', '0.6', 'Iris-setosa'], ['5.1', '3.8', '1.9', '0.4', 'Iris-setosa'], ['4.8', '3.0', '1.4', '0.3', 'Iris-setosa'], ['5.1', '3.8', '1.6', '0.2', 'Iris-setosa'], ['4.6', '3.2', '1.4', '0.2', 'Iris-setosa'], ['5.3', '3.7', '1.5', '0.2', 'Iris-setosa'], ['5.0', '3.3', '1.4', '0.2', 'Iris-setosa'], ['7.0', '3.2', '4.7', '1.4', 'Iris-versicolor'], ['6.4', '3.2', '4.5', '1.5', 'Iris-versicolor'], ['6.9', '3.1', '4.9', '1.5', 'Iris-versicolor'], ['5.5', '2.3', '4.0', '1.3', 'Iris-versicolor'], ['6.5', '2.8', '4.6', '1.5', 'Iris-versicolor'], ['5.7', '2.8', '4.5', '1.3', 'Iris-versicolor'], ['6.3', '3.3', '4.7', '1.6', 'Iris-versicolor'], ['4.9', '2.4', '3.3', '1.0', 'Iris-versicolor'], ['6.6', '2.9', '4.6', '1.3', 'Iris-versicolor'], ['5.2', '2.7', '3.9', '1.4', 'Iris-versicolor'], ['5.0', '2.0', '3.5', '1.0', 'Iris-versicolor'], ['5.9', '3.0', '4.2', '1.5', 'Iris-versicolor'], ['6.0', '2.2', '4.0', '1.0', 'Iris-versicolor'], ['6.1', '2.9', '4.7', '1.4', 'Iris-versicolor'], ['5.6', '2.9', '3.6', '1.3', 'Iris-versicolor'], ['6.7', '3.1', '4.4', '1.4', 'Iris-versicolor'], ['5.6', '3.0', '4.5', '1.5', 'Iris-versicolor'], ['5.8', '2.7', '4.1', '1.0', 'Iris-versicolor'], ['6.2', '2.2', '4.5', '1.5', 'Iris-versicolor'], ['5.6', '2.5', '3.9', '1.1', 'Iris-versicolor'], ['5.9', '3.2', '4.8', '1.8', 'Iris-versicolor'], ['6.1', '2.8', '4.0', '1.3', 'Iris-versicolor'], ['6.3', '2.5', '4.9', '1.5', 'Iris-versicolor'], ['6.1', '2.8', '4.7', '1.2', 'Iris-versicolor'], ['6.4', '2.9', '4.3', '1.3', 'Iris-versicolor'], ['6.6', '3.0', '4.4', '1.4', 'Iris-versicolor'], ['6.8', '2.8', '4.8', '1.4', 'Iris-versicolor'], ['6.7', '3.0', '5.0', '1.7', 'Iris-versicolor'], ['6.0', '2.9', '4.5', '1.5', 'Iris-versicolor'], ['5.7', '2.6', '3.5', '1.0', 'Iris-versicolor'], ['5.5', '2.4', '3.8', '1.1', 'Iris-versicolor'], ['5.5', '2.4', '3.7', '1.0', 'Iris-versicolor'], ['5.8', '2.7', '3.9', '1.2', 'Iris-versicolor'], ['6.0', '2.7', '5.1', '1.6', 'Iris-versicolor'], ['5.4', '3.0', '4.5', '1.5', 'Iris-versicolor'], ['6.0', '3.4', '4.5', '1.6', 'Iris-versicolor'], ['6.7', '3.1', '4.7', '1.5', 'Iris-versicolor'], ['6.3', '2.3', '4.4', '1.3', 'Iris-versicolor'], ['5.6', '3.0', '4.1', '1.3', 'Iris-versicolor'], ['5.5', '2.5', '4.0', '1.3', 'Iris-versicolor'], ['5.5', '2.6', '4.4', '1.2', 'Iris-versicolor'], ['6.1', '3.0', '4.6', '1.4', 'Iris-versicolor'], ['5.8', '2.6', '4.0', '1.2', 'Iris-versicolor'], ['5.0', '2.3', '3.3', '1.0', 'Iris-versicolor'], ['5.6', '2.7', '4.2', '1.3', 'Iris-versicolor'], ['5.7', '3.0', '4.2', '1.2', 'Iris-versicolor'], ['5.7', '2.9', '4.2', '1.3', 'Iris-versicolor'], ['6.2', '2.9', '4.3', '1.3', 'Iris-versicolor'], ['5.1', '2.5', '3.0', '1.1', 'Iris-versicolor'], ['5.7', '2.8', '4.1', '1.3', 'Iris-versicolor'], ['6.3', '3.3', '6.0', '2.5', 'Iris-virginica'], ['5.8', '2.7', '5.1', '1.9', 'Iris-virginica'], ['7.1', '3.0', '5.9', '2.1', 'Iris-virginica'], ['6.3', '2.9', '5.6', '1.8', 'Iris-virginica'], ['6.5', '3.0', '5.8', '2.2', 'Iris-virginica'], ['7.6', '3.0', '6.6', '2.1', 'Iris-virginica'], ['4.9', '2.5', '4.5', '1.7', 'Iris-virginica'], ['7.3', '2.9', '6.3', '1.8', 'Iris-virginica'], ['6.7', '2.5', '5.8', '1.8', 'Iris-virginica'], ['7.2', '3.6', '6.1', '2.5', 'Iris-virginica'], ['6.5', '3.2', '5.1', '2.0', 'Iris-virginica'], ['6.4', '2.7', '5.3', '1.9', 'Iris-virginica'], ['6.8', '3.0', '5.5', '2.1', 'Iris-virginica'], ['5.7', '2.5', '5.0', '2.0', 'Iris-virginica'], ['5.8', '2.8', '5.1', '2.4', 'Iris-virginica'], ['6.4', '3.2', '5.3', '2.3', 'Iris-virginica'], ['6.5', '3.0', '5.5', '1.8', 'Iris-virginica'], ['7.7', '3.8', '6.7', '2.2', 'Iris-virginica'], ['7.7', '2.6', '6.9', '2.3', 'Iris-virginica'], ['6.0', '2.2', '5.0', '1.5', 'Iris-virginica'], ['6.9', '3.2', '5.7', '2.3', 'Iris-virginica'], ['5.6', '2.8', '4.9', '2.0', 'Iris-virginica'], ['7.7', '2.8', '6.7', '2.0', 'Iris-virginica'], ['6.3', '2.7', '4.9', '1.8', 'Iris-virginica'], ['6.7', '3.3', '5.7', '2.1', 'Iris-virginica'], ['7.2', '3.2', '6.0', '1.8', 'Iris-virginica'], ['6.2', '2.8', '4.8', '1.8', 'Iris-virginica'], ['6.1', '3.0', '4.9', '1.8', 'Iris-virginica'], ['6.4', '2.8', '5.6', '2.1', 'Iris-virginica'], ['7.2', '3.0', '5.8', '1.6', 'Iris-virginica'], ['7.4', '2.8', '6.1', '1.9', 'Iris-virginica'], ['7.9', '3.8', '6.4', '2.0', 'Iris-virginica'], ['6.4', '2.8', '5.6', '2.2', 'Iris-virginica'], ['6.3', '2.8', '5.1', '1.5', 'Iris-virginica'], ['6.1', '2.6', '5.6', '1.4', 'Iris-virginica'], ['7.7', '3.0', '6.1', '2.3', 'Iris-virginica'], ['6.3', '3.4', '5.6', '2.4', 'Iris-virginica'], ['6.4', '3.1', '5.5', '1.8', 'Iris-virginica'], ['6.0', '3.0', '4.8', '1.8', 'Iris-virginica'], ['6.9', '3.1', '5.4', '2.1', 'Iris-virginica'], ['6.7', '3.1', '5.6', '2.4', 'Iris-virginica'], ['6.9', '3.1', '5.1', '2.3', 'Iris-virginica'], ['5.8', '2.7', '5.1', '1.9', 'Iris-virginica'], ['6.8', '3.2', '5.9', '2.3', 'Iris-virginica'], ['6.7', '3.3', '5.7', '2.5', 'Iris-virginica'], ['6.7', '3.0', '5.2', '2.3', 'Iris-virginica'], ['6.3', '2.5', '5.0', '1.9', 'Iris-virginica'], ['6.5', '3.0', '5.2', '2.0', 'Iris-virginica'], ['6.2', '3.4', '5.4', '2.3', 'Iris-virginica'], ['5.9', '3.0', '5.1', '1.8', 'Iris-virginica']]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "150"
+      ]
+     },
+     "execution_count": 180,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rawDataset =[]\n",
+    "\n",
+    "with open(\"iris.data\",\"r\",encoding=\"utf-8\") as file:\n",
+    "    for i in range(150):\n",
+    "        line = file.readline().strip(\"\\n\")\n",
+    "        line = line.split(\",\")\n",
+    "        rawDataset.append(line)\n",
+    "    \n",
+    "print(rawDataset)\n",
+    "len(rawDataset)\n",
+    "    \n",
+    "\n",
+    "   \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "n1 = Neuoron(\"Iris-setosa\")\n",
+    "n2 = Neuoron(\"Iris-versicolor\")\n",
+    "n3 = Neuoron(\"Iris-virginica\")\n",
+    "NeuralNetwork1 = NeuralNetwork(N1=n1, N2=n2, N3=n3)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[['5.1', '3.5', '1.4', '0.2', 'Iris-setosa'], ['4.9', '3.0', '1.4', '0.2', 'Iris-setosa'], ['4.7', '3.2', '1.3', '0.2', 'Iris-setosa'], ['4.6', '3.1', '1.5', '0.2', 'Iris-setosa'], ['5.0', '3.6', '1.4', '0.2', 'Iris-setosa'], ['5.4', '3.9', '1.7', '0.4', 'Iris-setosa'], ['4.6', '3.4', '1.4', '0.3', 'Iris-setosa'], ['5.0', '3.4', '1.5', '0.2', 'Iris-setosa'], ['4.4', '2.9', '1.4', '0.2', 'Iris-setosa'], ['4.9', '3.1', '1.5', '0.1', 'Iris-setosa'], ['5.4', '3.7', '1.5', '0.2', 'Iris-setosa'], ['4.8', '3.4', '1.6', '0.2', 'Iris-setosa'], ['4.8', '3.0', '1.4', '0.1', 'Iris-setosa'], ['4.3', '3.0', '1.1', '0.1', 'Iris-setosa'], ['5.8', '4.0', '1.2', '0.2', 'Iris-setosa'], ['5.7', '4.4', '1.5', '0.4', 'Iris-setosa'], ['5.4', '3.9', '1.3', '0.4', 'Iris-setosa'], ['5.1', '3.5', '1.4', '0.3', 'Iris-setosa'], ['5.7', '3.8', '1.7', '0.3', 'Iris-setosa'], ['5.1', '3.8', '1.5', '0.3', 'Iris-setosa'], ['5.4', '3.4', '1.7', '0.2', 'Iris-setosa'], ['5.1', '3.7', '1.5', '0.4', 'Iris-setosa'], ['4.6', '3.6', '1.0', '0.2', 'Iris-setosa'], ['5.1', '3.3', '1.7', '0.5', 'Iris-setosa'], ['4.8', '3.4', '1.9', '0.2', 'Iris-setosa'], ['5.0', '3.0', '1.6', '0.2', 'Iris-setosa'], ['5.0', '3.4', '1.6', '0.4', 'Iris-setosa'], ['5.2', '3.5', '1.5', '0.2', 'Iris-setosa'], ['5.2', '3.4', '1.4', '0.2', 'Iris-setosa'], ['4.7', '3.2', '1.6', '0.2', 'Iris-setosa'], ['4.8', '3.1', '1.6', '0.2', 'Iris-setosa'], ['5.4', '3.4', '1.5', '0.4', 'Iris-setosa'], ['5.2', '4.1', '1.5', '0.1', 'Iris-setosa'], ['5.5', '4.2', '1.4', '0.2', 'Iris-setosa'], ['4.9', '3.1', '1.5', '0.1', 'Iris-setosa'], ['5.0', '3.2', '1.2', '0.2', 'Iris-setosa'], ['5.5', '3.5', '1.3', '0.2', 'Iris-setosa'], ['4.9', '3.1', '1.5', '0.1', 'Iris-setosa'], ['4.4', '3.0', '1.3', '0.2', 'Iris-setosa'], ['5.1', '3.4', '1.5', '0.2', 'Iris-setosa'], ['5.0', '3.5', '1.3', '0.3', 'Iris-setosa'], ['4.5', '2.3', '1.3', '0.3', 'Iris-setosa'], ['4.4', '3.2', '1.3', '0.2', 'Iris-setosa'], ['5.0', '3.5', '1.6', '0.6', 'Iris-setosa'], ['5.1', '3.8', '1.9', '0.4', 'Iris-setosa'], ['4.8', '3.0', '1.4', '0.3', 'Iris-setosa'], ['5.1', '3.8', '1.6', '0.2', 'Iris-setosa'], ['4.6', '3.2', '1.4', '0.2', 'Iris-setosa'], ['5.3', '3.7', '1.5', '0.2', 'Iris-setosa'], ['5.0', '3.3', '1.4', '0.2', 'Iris-setosa'], ['7.0', '3.2', '4.7', '1.4', 'Iris-versicolor'], ['6.4', '3.2', '4.5', '1.5', 'Iris-versicolor'], ['6.9', '3.1', '4.9', '1.5', 'Iris-versicolor'], ['5.5', '2.3', '4.0', '1.3', 'Iris-versicolor'], ['6.5', '2.8', '4.6', '1.5', 'Iris-versicolor'], ['5.7', '2.8', '4.5', '1.3', 'Iris-versicolor'], ['6.3', '3.3', '4.7', '1.6', 'Iris-versicolor'], ['4.9', '2.4', '3.3', '1.0', 'Iris-versicolor'], ['6.6', '2.9', '4.6', '1.3', 'Iris-versicolor'], ['5.2', '2.7', '3.9', '1.4', 'Iris-versicolor'], ['5.0', '2.0', '3.5', '1.0', 'Iris-versicolor'], ['5.9', '3.0', '4.2', '1.5', 'Iris-versicolor'], ['6.0', '2.2', '4.0', '1.0', 'Iris-versicolor'], ['6.1', '2.9', '4.7', '1.4', 'Iris-versicolor'], ['5.6', '2.9', '3.6', '1.3', 'Iris-versicolor'], ['6.7', '3.1', '4.4', '1.4', 'Iris-versicolor'], ['5.6', '3.0', '4.5', '1.5', 'Iris-versicolor'], ['5.8', '2.7', '4.1', '1.0', 'Iris-versicolor'], ['6.2', '2.2', '4.5', '1.5', 'Iris-versicolor'], ['5.6', '2.5', '3.9', '1.1', 'Iris-versicolor'], ['5.9', '3.2', '4.8', '1.8', 'Iris-versicolor'], ['6.1', '2.8', '4.0', '1.3', 'Iris-versicolor'], ['6.3', '2.5', '4.9', '1.5', 'Iris-versicolor'], ['6.1', '2.8', '4.7', '1.2', 'Iris-versicolor'], ['6.4', '2.9', '4.3', '1.3', 'Iris-versicolor'], ['6.6', '3.0', '4.4', '1.4', 'Iris-versicolor'], ['6.8', '2.8', '4.8', '1.4', 'Iris-versicolor'], ['6.7', '3.0', '5.0', '1.7', 'Iris-versicolor'], ['6.0', '2.9', '4.5', '1.5', 'Iris-versicolor'], ['5.7', '2.6', '3.5', '1.0', 'Iris-versicolor'], ['5.5', '2.4', '3.8', '1.1', 'Iris-versicolor'], ['5.5', '2.4', '3.7', '1.0', 'Iris-versicolor'], ['5.8', '2.7', '3.9', '1.2', 'Iris-versicolor'], ['6.0', '2.7', '5.1', '1.6', 'Iris-versicolor'], ['5.4', '3.0', '4.5', '1.5', 'Iris-versicolor'], ['6.0', '3.4', '4.5', '1.6', 'Iris-versicolor'], ['6.7', '3.1', '4.7', '1.5', 'Iris-versicolor'], ['6.3', '2.3', '4.4', '1.3', 'Iris-versicolor'], ['5.6', '3.0', '4.1', '1.3', 'Iris-versicolor'], ['5.5', '2.5', '4.0', '1.3', 'Iris-versicolor'], ['5.5', '2.6', '4.4', '1.2', 'Iris-versicolor'], ['6.1', '3.0', '4.6', '1.4', 'Iris-versicolor'], ['5.8', '2.6', '4.0', '1.2', 'Iris-versicolor'], ['5.0', '2.3', '3.3', '1.0', 'Iris-versicolor'], ['5.6', '2.7', '4.2', '1.3', 'Iris-versicolor'], ['5.7', '3.0', '4.2', '1.2', 'Iris-versicolor'], ['5.7', '2.9', '4.2', '1.3', 'Iris-versicolor'], ['6.2', '2.9', '4.3', '1.3', 'Iris-versicolor'], ['5.1', '2.5', '3.0', '1.1', 'Iris-versicolor'], ['5.7', '2.8', '4.1', '1.3', 'Iris-versicolor'], ['6.3', '3.3', '6.0', '2.5', 'Iris-virginica'], ['5.8', '2.7', '5.1', '1.9', 'Iris-virginica'], ['7.1', '3.0', '5.9', '2.1', 'Iris-virginica'], ['6.3', '2.9', '5.6', '1.8', 'Iris-virginica'], ['6.5', '3.0', '5.8', '2.2', 'Iris-virginica'], ['7.6', '3.0', '6.6', '2.1', 'Iris-virginica'], ['4.9', '2.5', '4.5', '1.7', 'Iris-virginica'], ['7.3', '2.9', '6.3', '1.8', 'Iris-virginica'], ['6.7', '2.5', '5.8', '1.8', 'Iris-virginica'], ['7.2', '3.6', '6.1', '2.5', 'Iris-virginica'], ['6.5', '3.2', '5.1', '2.0', 'Iris-virginica'], ['6.4', '2.7', '5.3', '1.9', 'Iris-virginica'], ['6.8', '3.0', '5.5', '2.1', 'Iris-virginica'], ['5.7', '2.5', '5.0', '2.0', 'Iris-virginica'], ['5.8', '2.8', '5.1', '2.4', 'Iris-virginica'], ['6.4', '3.2', '5.3', '2.3', 'Iris-virginica'], ['6.5', '3.0', '5.5', '1.8', 'Iris-virginica'], ['7.7', '3.8', '6.7', '2.2', 'Iris-virginica'], ['7.7', '2.6', '6.9', '2.3', 'Iris-virginica'], ['6.0', '2.2', '5.0', '1.5', 'Iris-virginica'], ['6.9', '3.2', '5.7', '2.3', 'Iris-virginica'], ['5.6', '2.8', '4.9', '2.0', 'Iris-virginica'], ['7.7', '2.8', '6.7', '2.0', 'Iris-virginica'], ['6.3', '2.7', '4.9', '1.8', 'Iris-virginica'], ['6.7', '3.3', '5.7', '2.1', 'Iris-virginica'], ['7.2', '3.2', '6.0', '1.8', 'Iris-virginica'], ['6.2', '2.8', '4.8', '1.8', 'Iris-virginica'], ['6.1', '3.0', '4.9', '1.8', 'Iris-virginica'], ['6.4', '2.8', '5.6', '2.1', 'Iris-virginica'], ['7.2', '3.0', '5.8', '1.6', 'Iris-virginica'], ['7.4', '2.8', '6.1', '1.9', 'Iris-virginica'], ['7.9', '3.8', '6.4', '2.0', 'Iris-virginica'], ['6.4', '2.8', '5.6', '2.2', 'Iris-virginica'], ['6.3', '2.8', '5.1', '1.5', 'Iris-virginica'], ['6.1', '2.6', '5.6', '1.4', 'Iris-virginica'], ['7.7', '3.0', '6.1', '2.3', 'Iris-virginica'], ['6.3', '3.4', '5.6', '2.4', 'Iris-virginica'], ['6.4', '3.1', '5.5', '1.8', 'Iris-virginica'], ['6.0', '3.0', '4.8', '1.8', 'Iris-virginica'], ['6.9', '3.1', '5.4', '2.1', 'Iris-virginica'], ['6.7', '3.1', '5.6', '2.4', 'Iris-virginica'], ['6.9', '3.1', '5.1', '2.3', 'Iris-virginica'], ['5.8', '2.7', '5.1', '1.9', 'Iris-virginica'], ['6.8', '3.2', '5.9', '2.3', 'Iris-virginica'], ['6.7', '3.3', '5.7', '2.5', 'Iris-virginica'], ['6.7', '3.0', '5.2', '2.3', 'Iris-virginica'], ['6.3', '2.5', '5.0', '1.9', 'Iris-virginica'], ['6.5', '3.0', '5.2', '2.0', 'Iris-virginica'], ['6.2', '3.4', '5.4', '2.3', 'Iris-virginica'], ['5.9', '3.0', '5.1', '1.8', 'Iris-virginica']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(rawDataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 176,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Iris-setosa -- [0.9, 0.492, 0.943, 0.08]\n",
+      "Iris-versicolor -- [0.85, 0.054, 0.745, 0.927]\n",
+      "Iris-virginica -- [0.06, 0.003, 0.605, 0.036]\n",
+      "yüzde 0.0 dogru biliyor\n",
+      "Iris-setosa -- [0.6799999999999998, 0.2719999999999998, 0.7229999999999998, -0.13999999999999999]\n",
+      "Iris-versicolor -- [0.7099999999999999, -0.08600000000000001, 0.6049999999999999, 0.7869999999999999]\n",
+      "Iris-virginica -- [0.4200000000000002, 0.36300000000000016, 0.9650000000000003, 0.3960000000000002]\n",
+      "yüzde 94.83333333333334 dogru biliyor\n"
+     ]
+    }
+   ],
+   "source": [
+    "n1 = Neuoron(\"Iris-setosa\")\n",
+    "n2 = Neuoron(\"Iris-versicolor\")\n",
+    "n3 = Neuoron(\"Iris-virginica\")\n",
+    "NeuralNetwork1 = NeuralNetwork(N1=n1, N2=n2, N3=n3)\n",
+    "NeuralNetwork1.output()\n",
+    "NeuralNetwork1.train(RawDataset=rawDataset, landa=0.01,epok=20)\n",
+    "NeuralNetwork1.output()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Iris-setosa -- [0.40000000000000013, 0.2770000000000001, 0.5870000000000002, 0.6640000000000001]\n",
+      "Iris-versicolor -- [0.2989999999999999, 0.5389999999999999, 0.6309999999999999, 0.5429999999999999]\n",
+      "Iris-virginica -- [0.597, 0.6629999999999999, 0.22199999999999992, 0.717]\n",
+      "yüzde 80.83333333333333 dogru biliyor\n"
+     ]
+    }
+   ],
+   "source": [
+    "NeuralNetwork1.output()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.8 64-bit (microsoft store)",
+   "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": "3.10.8"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "8db4cba391c77a0d062dd389646739933a0357c2fea870a048a001ec86814760"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/neuron.py b/neuron.py
new file mode 100644
index 0000000..e69de29