Coursera Deep Learning W2 - Vectorization Demo.ipynb

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      "[1 2 3 4]\n"
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   "source": [
    "import numpy as np\n",
    "\n",
    "a = np.array([1,2,3,4])\n",
    "print(a)"
   ]
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   "metadata": {},
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      "249822.532493\n",
      "Vectorized version:0.990867614746ms\n",
      "\n",
      "249822.532493\n",
      "For loop:487.673044205ms\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "\n",
    "a = np.random.rand(1000000)\n",
    "b = np.random.rand(1000000)\n",
    "\n",
    "tic = time.time()\n",
    "c = np.dot(a,b)\n",
    "toc = time.time()\n",
    "\n",
    "print(c)\n",
    "print(\"Vectorized version:\" + str(1000*(toc-tic)) + \"ms\")\n",
    "\n",
    "c = 0\n",
    "tic = time.time()\n",
    "for i in range(1000000):\n",
    "    c += a[i]*b[i]\n",
    "toc = time.time()\n",
    "\n",
    "print \"\"\n",
    "print(c)\n",
    "print(\"For loop:\" + str(1000*(toc-tic)) + \"ms\")"
   ]
  },
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