Lab 3 - fix doctoring for 2c, fix variable name for 3c

lab3_text_analysis_and_entity_resolution_student.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "version 1.0.2\n",
+    "version 1.0.3\n",
     "#![Spark Logo](http://spark-mooc.github.io/web-assets/images/ta_Spark-logo-small.png) + ![Python Logo](http://spark-mooc.github.io/web-assets/images/python-logo-master-v3-TM-flattened_small.png)\n",
     "# **Text Analysis and Entity Resolution**\n",
     "####Entity resolution is a common, yet difficult problem in data cleaning and integration. This lab will demonstrate how we can use Apache Spark to apply powerful and scalable text analysis techniques and perform entity resolution across two datasets of commercial products."
@@ -523,7 +523,7 @@
     "    Args:\n",
     "        corpus (RDD): input corpus\n",
     "    Returns:\n",
-    "        RDD: a RDD of (record ID, IDF value)\n",
+    "        RDD: a RDD of (token, IDF value)\n",
     "    \"\"\"\n",
     "    N = <FILL IN>\n",
     "    uniqueTokens = corpus.<FILL IN>\n",
@@ -837,7 +837,7 @@
     "    amazonID = <FILL IN>\n",
     "    googleValue = <FILL IN>\n",
     "    amazonValue = <FILL IN>\n",
-    "    cs = cosineSimilarity(<FILL IN>, idfs_small_weights)\n",
+    "    cs = cosineSimilarity(<FILL IN>, idfsSmallWeights)\n",
     "    return (googleURL, amazonID, cs)\n",
     "\n",
     "similarities = (crossSmall\n",