Update week37.ipynb

doc/pub/week37/ipynb/week37.ipynb

@@ -3518,7 +3518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 6,
    "id": "2ed0cafc",
    "metadata": {
     "collapsed": false,
@@ -3539,12 +3539,12 @@
       "0.004113634617443139\n",
       "MSE with intercept column from SKL\n",
       "0.004113634617443147\n",
-      "Manual intercept: 2.083766322923907\n",
+      "Manual intercept: 2.083766322923899\n",
       "Fitted theta (without intercept): [0.19569961 3.97898392]\n",
       "Sklearn intercept: 2.0837663229239043\n",
       "Sklearn fitted theta (without intercept): [0.19569961 3.97898392]\n",
       "MSE with Manual intercept\n",
-      "4.346195723169266\n",
+      "0.00411363461744314\n",
       "MSE with Sklearn intercept\n",
       "0.004113634617443131\n"
      ]
@@ -3627,7 +3627,7 @@
     "y_offset = np.average(y, axis=0)\n",
     "X_offset = np.average(X, axis=0)\n",
     "\n",
-    "theta = fit_theta(X - X_offset, y)#-y_offset)\n",
+    "theta = fit_theta(X - X_offset, y-y_offset)\n",
     "intercept = np.mean(y_offset - X_offset @ theta)\n",
     "\n",
     "print(f\"Manual intercept: {intercept}\")\n",
@@ -3637,7 +3637,7 @@
     "ypredictOwn = X @ theta\n",
     "ypredictSKL = skl.predict(X)\n",
     "print(f\"MSE with Manual intercept\")\n",
-    "print(MSE(y,ypredictOwn))#+intercept))\n",
+    "print(MSE(y,ypredictOwn+intercept))\n",
     "print(f\"MSE with Sklearn intercept\")\n",
     "print(MSE(y,ypredictSKL))\n",
     "\n",
@@ -3745,7 +3745,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 4,
    "id": "4f9b1fa0",
    "metadata": {
     "collapsed": false,
@@ -3943,7 +3943,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 5,
    "id": "a731e32c",
    "metadata": {
     "collapsed": false,