chapter_4_alpha.ipynb

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    "weight = 0.5\n",
    "goal_pred = 0.8\n",
    "input = 2\n",
    "alpha = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error: 0.03999999999999998  Pred: 1.0\n",
      "Error: 0.0144  Pred: 0.92\n",
      "Error: 0.005183999999999993  Pred: 0.872\n",
      "Error: 0.0018662400000000014  Pred: 0.8432000000000001\n",
      "Error: 0.0006718464000000028  Pred: 0.8259200000000001\n",
      "Error: 0.00024186470400000033  Pred: 0.815552\n",
      "Error: 8.70712934399997e-05  Pred: 0.8093312\n",
      "Error: 3.134566563839939e-05  Pred: 0.80559872\n",
      "Error: 1.1284439629823931e-05  Pred: 0.803359232\n",
      "Error: 4.062398266736526e-06  Pred: 0.8020155392\n",
      "Error: 1.4624633760252567e-06  Pred: 0.8012093235200001\n",
      "Error: 5.264868153690924e-07  Pred: 0.8007255941120001\n",
      "Error: 1.8953525353291194e-07  Pred: 0.8004353564672001\n",
      "Error: 6.82326912718715e-08  Pred: 0.8002612138803201\n",
      "Error: 2.456376885786678e-08  Pred: 0.8001567283281921\n",
      "Error: 8.842956788836216e-09  Pred: 0.8000940369969153\n",
      "Error: 3.1834644439835434e-09  Pred: 0.8000564221981492\n",
      "Error: 1.1460471998340758e-09  Pred: 0.8000338533188895\n",
      "Error: 4.125769919393652e-10  Pred: 0.8000203119913337\n",
      "Error: 1.485277170987127e-10  Pred: 0.8000121871948003\n"
     ]
    }
   ],
   "source": [
    "for iteration in range(20):\n",
    "    pred = input * weight\n",
    "    error = (pred - goal_pred) ** 2\n",
    "    derivative = input * (pred - goal_pred)\n",
    "    weight = weight - (alpha * derivative)\n",
    "    print(\"Error:\",error,\" Pred:\",pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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