From 015a34e3d47a5d1e15ca42a4f58edf1f50a13efc Mon Sep 17 00:00:00 2001
From: udlbook <110402648+udlbook@users.noreply.github.com>
Date: Tue, 25 Oct 2022 11:44:09 +0100
Subject: [PATCH] Created using Colaboratory

---
 CM20315_Loss_II.ipynb | 38 +++++++++++++++++++-------------------
 1 file changed, 19 insertions(+), 19 deletions(-)

diff --git a/CM20315_Loss_II.ipynb b/CM20315_Loss_II.ipynb
index 3749a06..b3ff145 100644
--- a/CM20315_Loss_II.ipynb
+++ b/CM20315_Loss_II.ipynb
@@ -5,7 +5,7 @@
     "colab": {
       "provenance": [],
       "collapsed_sections": [],
-      "authorship_tag": "ABX9TyPBGTxs29MOs80wv5LpyIcV",
+      "authorship_tag": "ABX9TyOE0qm8aIpEaNh/aI9gnlkY",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -244,24 +244,6 @@
         "id": "R5z_0dzQMF35"
       }
     },
-    {
-      "cell_type": "code",
-      "source": [
-        "# Return the likelihood of all of the data under the model\n",
-        "def compute_likelihood(y_train, lambda_param):\n",
-        "  # TODO -- compute the likelihood of the data -- the product of the normal probabilities for each data point\n",
-        "  # Top line of equation 5.3 in the notes\n",
-        "  # You will need np.prod() and the normal_distribution function you used above\n",
-        "  # Replace the line below\n",
-        "  likelihood = 0\n",
-        "  return likelihood"
-      ],
-      "metadata": {
-        "id": "zpS7o6liCx7f"
-      },
-      "execution_count": null,
-      "outputs": []
-    },
     {
       "cell_type": "code",
       "source": [
@@ -339,6 +321,24 @@
         "id": "OgcRojvPWh4V"
       }
     },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Return the likelihood of all of the data under the model\n",
+        "def compute_likelihood(y_train, lambda_param):\n",
+        "  # TODO -- compute the likelihood of the data -- the product of the Bernoulli probabilities for each data point\n",
+        "  # Top line of equation 5.3 in the notes\n",
+        "  # You will need np.prod() and the bernoulli_distribution function you used above\n",
+        "  # Replace the line below\n",
+        "  likelihood = 0\n",
+        "  return likelihood"
+      ],
+      "metadata": {
+        "id": "zpS7o6liCx7f"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
     {
       "cell_type": "code",
       "source": [