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Jean-KOUAGOU · Nov 12, 2019 · f1594f5 · f1594f5
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diff --git a/Jean-N'dah_perceptron.ipynb b/Jean-N'dah_perceptron.ipynb
diff --git a/My-Logistic-regression.ipynb b/My-Logistic-regression.ipynb
diff --git a/My_binary_search_from_scratch.ipynb b/My_binary_search_from_scratch.ipynb
@@ -0,0 +1,113 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Length of the current array: 10\n",
+      "Length of the current array: 4\n",
+      "Length of the current array: 2\n",
+      "Length of the current array: 1\n",
+      "\n",
+      "-1\n",
+      "\n",
+      "Length of the current array: 10\n",
+      "Length of the current array: 4\n",
+      "\n",
+      "8\n"
+     ]
+    }
+   ],
+   "source": [
+    "\"\"\"You're going to write a binary search function.\n",
+    "You should use an iterative approach - meaning\n",
+    "using loops.\n",
+    "Your function should take two inputs:\n",
+    "a Python list to search through, and the value\n",
+    "you're searching for.\n",
+    "Assume the list only has distinct elements,\n",
+    "meaning there are no repeated values, and \n",
+    "elements are in a strictly increasing order.\n",
+    "Return the index of value, or -1 if the value\n",
+    "doesn't exist in the list.\"\"\"\n",
+    "import numpy as np\n",
+    "\n",
+    "def binary_search_helper(input_array):\n",
+    "    \"\"\"Your code goes here.\"\"\"\n",
+    "    n=len(input_array)\n",
+    "    even=False\n",
+    "    if n%2==0:\n",
+    "        center=n//2\n",
+    "        even=True\n",
+    "    else:\n",
+    "        center=(n-1)//2\n",
+    "    return center, even\n",
+    "    \n",
+    "def binary_search(input_array, value):\n",
+    "    index=-1\n",
+    "    Search=True\n",
+    "    center=binary_search_helper(input_array)[0]\n",
+    "    position=center\n",
+    "    while(index==-1 and Search):\n",
+    "        print(\"Length of the current array:\",len(input_array))\n",
+    "        if input_array[center]>value:\n",
+    "            input_array=input_array[:center]\n",
+    "            center, even_left=binary_search_helper(input_array)\n",
+    "            if even_left:\n",
+    "                position -= center\n",
+    "            else:\n",
+    "                position -= center+1\n",
+    "        elif input_array[center]<value:\n",
+    "            input_array=input_array[center+1:]\n",
+    "            center, even_left=binary_search_helper(input_array)\n",
+    "            position += center+1\n",
+    "        elif input_array[center]==value:\n",
+    "            index=position\n",
+    "        if len(input_array)==0:\n",
+    "            Search=False\n",
+    "    print()\n",
+    "    return index\n",
+    "test_list = [1,3,9,11,15,19,29,171,527.7,1472]\n",
+    "test_val1 = 25\n",
+    "test_val2 = 527.7\n",
+    "print(binary_search(test_list, test_val1))\n",
+    "print()\n",
+    "\n",
+    "print(binary_search(test_list, test_val2))"
+   ]
+  },
+  {
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}