updated hopfield network and SAM model template notebooks, added SAM template to TOC

Author: jeremymanning

content/_toc.yml

@@ -35,6 +35,8 @@ parts:
         sections:
         - file: assignments/Assignment_1:Hopfield_Networks/hopfield_assignment_template
       - file: assignments/Assignment_2:Search_of_Associative_Memory_Model/README
+        sections:
+        - file: assignments/Assignment_2:Search_of_Associative_Memory_Model/sam_assignment_template
       - file: assignments/Assignment_3:Context_Maintenance_and_Retrieval_Model/README
       - file: assignments/Assignment_4:_Laplace_Temporal_Context_Model/README
       - file: assignments/Final_Project/README

content/assignments/Assignment_1:Hopfield_Networks/hopfield_assignment_template.ipynb

@@ -22,7 +22,7 @@
         "\n",
         "This notebook provides a suggested starter template for completing the [Hopfield network assignment](https://contextlab.github.io/memory-models-course/assignments/Assignment_1%3AHopfield_Networks/README.html).\n",
         "\n",
-        "You should submit your assignment by uploading your completed notebook to [Canvas](https://canvas.dartmouth.edu/courses/71051/assignments/517353).  Please ensure that your notebook runs without errors in [Google Colaborator](https://colab.research.google.com/)."
+        "You should submit your assignment by uploading your completed notebook to [Canvas](https://canvas.dartmouth.edu/courses/71051/assignments/517353).  Please ensure that your notebook runs without errors in [Google Colaboratory](https://colab.research.google.com/)."
       ]
     },
     {

content/assignments/Assignment_2:Search_of_Associative_Memory_Model/sam_assignment_template.ipynb

@@ -1,38 +1,34 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
-    "colab": {
-      "provenance": [],
-      "include_colab_link": true
-    },
-    "kernelspec": {
-      "name": "python3",
-      "display_name": "Python 3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
   "cells": [
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "colab_type": "text",
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/ContextLab/memory-models-course/blob/main/content/Assignment_2%3ASearch_of_Associative_Memory_Model/sam_assignment_template.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
       "cell_type": "markdown",
+      "metadata": {},
       "source": [
-        "Imports"
-      ],
+        "# Submission Template\n",
+        "\n",
+        "This notebook provides a suggested starter template for completing the [SAM model assignment](https://contextlab.github.io/memory-models-course/assignments/Assignment_2%3ASearch_of_Associative_Memory_Model/README.html).\n",
+        "\n",
+        "You should submit your assignment by uploading your completed notebook to [Canvas](https://canvas.dartmouth.edu/courses/71051/assignments/517354).  Please ensure that your notebook runs without errors in [Google Colaboratory](https://colab.research.google.com/)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
       "metadata": {
         "id": "ZNp6i_sXKA8r"
-      }
+      },
+      "source": [
+        "Imports"
+      ]
     },
     {
       "cell_type": "code",
@@ -50,15 +46,20 @@
     },
     {
       "cell_type": "markdown",
-      "source": [
-        "Basic skeleton for the SAM model"
-      ],
       "metadata": {
         "id": "atpXuzOFKDSb"
-      }
+      },
+      "source": [
+        "Basic skeleton for the SAM model"
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "PUXuEy_3-q3E"
+      },
+      "outputs": [],
       "source": [
         "class item(object):\n",
         "  count = 0\n",
@@ -132,28 +133,38 @@
         "    #    - recall (given cue strength):\n",
         "    #       - if successful, reset m1_count and m2_count, set previous_recall to item, return sampled item\n",
         "    #       - otherwise increment m1_count or m2_count.  if either exceed M_1/M2, return None"
-      ],
-      "metadata": {
-        "id": "PUXuEy_3-q3E"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "ipssh_MdXWF8"
+      },
       "source": [
         "Other tasks:\n",
-        "  - Fit params to [Murdock (1962) dataset](https://memory.psych.upenn.edu/files/pubs/Murd62.data.tgz)\n",
+        "  - Fit params to [Murdock (1962) dataset](https://github.com/ContextLab/memory-models-course/tree/main/content/assignments/Assignment_2%3ASearch_of_Associative_Memory_Model/Murd62%20data)\n",
         "     - Need to define a \"loss\" function.  I suggest computing MSE for one or more behavioral curves, computed for a subset of the Murdock (1962) participants/lists\n",
         "     - I suggest using [scipy.optimize.minimize](https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html) to estimate the model parameters.\n",
         "  - Create observed/predicted plots for held-out data:\n",
         "     - p(first recall)\n",
         "     - p(recall)\n",
         "     - lag-CRP"
-      ],
-      "metadata": {
-        "id": "ipssh_MdXWF8"
-      }
+      ]
     }
-  ]
-}
+  ],
+  "metadata": {
+    "colab": {
+      "include_colab_link": true,
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}