Ch03_3_5.ipynb

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    "weights = [0.1, 0.2, 0]\n",
    "\n",
    "def neural_network(input, weights):\n",
    "    \n",
    "    pred = w_sum(input, weights)\n",
    "    \n",
    "    return pred\n",
    "\n",
    "def w_sum(a, b):\n",
    "    \n",
    "    assert(len(a) == len(b))\n",
    "    \n",
    "    output = 0\n",
    "    \n",
    "    for i in range(len(a)):\n",
    "        \n",
    "        output += (a[i] * b[i])\n",
    "        \n",
    "    return output"
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      "0.9800000000000001\n"
     ]
    }
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   "source": [
    "# This dataset is the current\n",
    "# status at the beginning of\n",
    "# each game for the first 4 games\n",
    "# in a season.\n",
    "\n",
    "# toes = current number of toes\n",
    "# wlrec = current games won (percent)\n",
    "# nfans = fan count (in millions ) \n",
    "\n",
    "toes = [8.5, 9.5, 9.9, 9.0]\n",
    "wlrec = [0.65, 0.8, 0.8, 0.9]\n",
    "nfans = [1.2, 1.3, 0.5, 1.0]\n",
    "\n",
    "# input corresponds to every entry\n",
    "# for the first game of the season\n",
    "\n",
    "input = [toes[0], wlrec[0], nfans[0]]\n",
    "\n",
    "pred = neural_network(input, weights)\n",
    "\n",
    "print(pred)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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