diff --git a/sentiment-network/Sentiment_Classification_Projects.ipynb b/sentiment-network/Sentiment_Classification_Projects.ipynb
index 21addf4de5..7e56d299b3 100644
--- a/sentiment-network/Sentiment_Classification_Projects.ipynb
+++ b/sentiment-network/Sentiment_Classification_Projects.ipynb
@@ -77,6 +77,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "nbpresent": {
      "id": "eba2b193-0419-431e-8db9-60f34dd3fe83"
     }
@@ -105,7 +106,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "len(reviews)"
@@ -115,6 +118,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "nbpresent": {
      "id": "bb95574b-21a0-4213-ae50-34363cf4f87f"
     }
@@ -128,6 +132,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "nbpresent": {
      "id": "e0408810-c424-4ed4-afb9-1735e9ddbd0a"
     }
@@ -148,6 +153,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "nbpresent": {
      "id": "e67a709f-234f-4493-bae6-4fb192141ee0"
     }
@@ -196,7 +202,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# Create three Counter objects to store positive, negative and total counts\n",
@@ -318,11 +326,9 @@
     "\n",
     "To fix these issues, we'll convert all of our ratios to new values using logarithms.\n",
     "\n",
-    "**TODO:** Go through all the ratios you calculated and convert their values using the following formulas:\n",
-    "> * For any postive words, convert the ratio using `np.log(ratio)`\n",
-    "> * For any negative words, convert the ratio using `-np.log(1/(ratio + 0.01))`\n",
+    "**TODO:** Go through all the ratios you calculated and convert them to logarithms. (i.e. use `np.log(ratio)`)\n",
     "\n",
-    "That second equation may look strange, but what it's doing is dividing one by a very small number, which will produce a larger positive number. Then, it takes the `log` of that, which produces numbers similar to the ones for the postive words. Finally, we negate the values by adding that minus sign up front. In the end, extremely positive and extremely negative words will have positive-to-negative ratios with similar magnitudes but oppositite signs."
+    "In the end, extremely positive and extremely negative words will have positive-to-negative ratios with similar magnitudes but opposite signs."
    ]
   },
   {
@@ -415,7 +421,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from IPython.display import Image\n",
@@ -428,7 +436,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "review = \"The movie was excellent\"\n",
@@ -448,7 +458,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# TODO: Create set named \"vocab\" containing all of the words from all of the reviews\n",
@@ -484,7 +496,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -543,7 +557,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from IPython.display import Image\n",
@@ -1082,7 +1098,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from IPython.display import Image\n",
@@ -1854,7 +1872,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [default]",
    "language": "python",
    "name": "python3"
   },
@@ -1868,7 +1886,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.3"
+   "version": "3.5.2"
   }
  },
  "nbformat": 4,
diff --git a/sentiment-network/Sentiment_Classification_Solutions.ipynb b/sentiment-network/Sentiment_Classification_Solutions.ipynb
index b9ac4ca1ee..2a066e96a9 100644
--- a/sentiment-network/Sentiment_Classification_Solutions.ipynb
+++ b/sentiment-network/Sentiment_Classification_Solutions.ipynb
@@ -77,6 +77,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
+    "collapsed": true,
     "nbpresent": {
      "id": "eba2b193-0419-431e-8db9-60f34dd3fe83"
     }
@@ -105,7 +106,9 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -126,6 +129,7 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
+    "collapsed": false,
     "nbpresent": {
      "id": "bb95574b-21a0-4213-ae50-34363cf4f87f"
     }
@@ -150,6 +154,7 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
+    "collapsed": false,
     "nbpresent": {
      "id": "e0408810-c424-4ed4-afb9-1735e9ddbd0a"
     }
@@ -181,6 +186,7 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
+    "collapsed": false,
     "nbpresent": {
      "id": "e67a709f-234f-4493-bae6-4fb192141ee0"
     }
@@ -225,7 +231,9 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from collections import Counter\n",
@@ -292,7 +300,9 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -1313,7 +1323,9 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -2344,7 +2356,9 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "pos_neg_ratios = Counter()\n",
@@ -2367,7 +2381,9 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2402,11 +2418,9 @@
     "\n",
     "To fix these issues, we'll convert all of our ratios to new values using logarithms.\n",
     "\n",
-    "**TODO:** Go through all the ratios you calculated and convert their values using the following formulas:\n",
-    "> * For any postive words, convert the ratio using `np.log(ratio)`\n",
-    "> * For any negative words, convert the ratio using `-np.log(1/(ratio + 0.01))`\n",
+    "**TODO:** Go through all the ratios you calculated and convert them to logarithms. (i.e. use `np.log(ratio)`)\n",
     "\n",
-    "That second equation may look strange, but what it's doing is dividing one by a very small number, which will produce a larger positive number. Then, it takes the `log` of that, which produces numbers similar to the ones for the postive words. Finally, we negate the values by adding that minus sign up front. In the end, extremely positive and extremely negative words will have positive-to-negative ratios with similar magnitudes but oppositite signs."
+    "In the end, extremely positive and extremely negative words will have positive-to-negative ratios with similar magnitudes but opposite signs."
    ]
   },
   {
@@ -2419,10 +2433,18 @@
    "source": [
     "# Convert ratios to logs\n",
     "for word,ratio in pos_neg_ratios.most_common():\n",
-    "    if(ratio > 1):\n",
-    "        pos_neg_ratios[word] = np.log(ratio)\n",
-    "    else:\n",
-    "        pos_neg_ratios[word] = -np.log((1 / (ratio+0.01)))"
+    "    pos_neg_ratios[word] = np.log(ratio)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**NOTE:** In the video, Andrew uses the following formulas for the previous cell:\n",
+    "> * For any postive words, convert the ratio using `np.log(ratio)`\n",
+    "> * For any negative words, convert the ratio using `-np.log(1/(ratio + 0.01))`\n",
+    "\n",
+    "These won't give you the exact same results as the simpler code we show in this notebook, but the values will be similar. In case that second equation looks strange, here's what it's doing: First, it divides one by a very small number, which will produce a larger positive number. Then, it takes the `log` of that, which produces numbers similar to the ones for the postive words. Finally, it negates the values by adding that minus sign up front. The results are extremely positive and extremely negative words having positive-to-negative ratios with similar magnitudes but oppositite signs, just like when we use `np.log(ratio)`."
    ]
   },
   {
@@ -2435,7 +2457,9 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2443,7 +2467,7 @@
      "text": [
       "Pos-to-neg ratio for 'the' = 0.05902269426102881\n",
       "Pos-to-neg ratio for 'amazing' = 1.3919815802404802\n",
-      "Pos-to-neg ratio for 'terrible' = -1.6742829939664696\n"
+      "Pos-to-neg ratio for 'terrible' = -1.7291085042663878\n"
      ]
     }
    ],
@@ -2471,7 +2495,9 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -3493,42 +3519,43 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[('boll', -4.0778152602708904),\n",
-       " ('uwe', -3.9218753018711578),\n",
-       " ('seagal', -3.3202501058581921),\n",
-       " ('unwatchable', -3.0269848170580955),\n",
-       " ('stinker', -2.9876839403711624),\n",
-       " ('mst', -2.7753833211707968),\n",
-       " ('incoherent', -2.7641396677532537),\n",
-       " ('unfunny', -2.5545257844967644),\n",
-       " ('waste', -2.4907515123361046),\n",
-       " ('blah', -2.4475792789485005),\n",
-       " ('horrid', -2.3715779644809971),\n",
-       " ('pointless', -2.3451073877136341),\n",
-       " ('atrocious', -2.3187369339642556),\n",
-       " ('redeeming', -2.2667790015910296),\n",
-       " ('prom', -2.2601040980178784),\n",
-       " ('drivel', -2.2476029585766928),\n",
-       " ('lousy', -2.2118080125207054),\n",
-       " ('worst', -2.1930856334332267),\n",
-       " ('laughable', -2.172468615469592),\n",
-       " ('awful', -2.1385076866397488),\n",
-       " ('poorly', -2.1326133844207011),\n",
-       " ('wasting', -2.1178155545614512),\n",
-       " ('remotely', -2.111046881095167),\n",
-       " ('existent', -2.0024805005437076),\n",
-       " ('boredom', -1.9241486572738005),\n",
-       " ('miserably', -1.9216610938019989),\n",
-       " ('sucks', -1.9166645809588516),\n",
-       " ('uninspired', -1.9131499212248517),\n",
-       " ('lame', -1.9117232884159072),\n",
-       " ('insult', -1.9085323769376259)]"
+       "[('boll', -4.9698132995760007),\n",
+       " ('uwe', -4.6249728132842707),\n",
+       " ('seagal', -3.6441435602725449),\n",
+       " ('unwatchable', -3.2580965380214821),\n",
+       " ('stinker', -3.2088254890146994),\n",
+       " ('mst', -2.9502698994772336),\n",
+       " ('incoherent', -2.9368917735310576),\n",
+       " ('unfunny', -2.6922395950755678),\n",
+       " ('waste', -2.6193845640165536),\n",
+       " ('blah', -2.5704288232261625),\n",
+       " ('horrid', -2.4849066497880004),\n",
+       " ('pointless', -2.4553061800117097),\n",
+       " ('atrocious', -2.4259083090260445),\n",
+       " ('redeeming', -2.3682390632154826),\n",
+       " ('prom', -2.3608540011180215),\n",
+       " ('drivel', -2.3470368555648795),\n",
+       " ('lousy', -2.3075726345050849),\n",
+       " ('worst', -2.2869878961803778),\n",
+       " ('laughable', -2.2643638801738479),\n",
+       " ('awful', -2.2271942470274348),\n",
+       " ('poorly', -2.2207550747464135),\n",
+       " ('wasting', -2.2046046846338418),\n",
+       " ('remotely', -2.1972245773362196),\n",
+       " ('existent', -2.0794415416798357),\n",
+       " ('boredom', -1.9951003932460849),\n",
+       " ('miserably', -1.9924301646902063),\n",
+       " ('sucks', -1.9870682215488209),\n",
+       " ('uninspired', -1.9832976811269336),\n",
+       " ('lame', -1.981767458946166),\n",
+       " ('insult', -1.9783454248084671)]"
       ]
      },
      "execution_count": 16,
@@ -3560,7 +3587,9 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -3585,7 +3614,9 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -3637,7 +3668,9 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -3662,7 +3695,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -3709,7 +3744,9 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -3729,7 +3766,9 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -3758,1011 +3797,1013 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "{'': 0,\n",
-       " 'newmail': 1,\n",
-       " 'reaganism': 2,\n",
-       " 'electrifying': 3,\n",
-       " 'warecki': 4,\n",
-       " 'hamilton': 5,\n",
-       " 'hearkens': 6,\n",
-       " 'nella': 7,\n",
-       " 'snort': 8,\n",
-       " 'imitation': 9,\n",
-       " 'cunda': 10,\n",
-       " 'ebon': 11,\n",
-       " 'weldon': 12,\n",
-       " 'lovable': 13,\n",
-       " 'wargaming': 14,\n",
-       " 'rivero': 15,\n",
-       " 'ackerman': 16,\n",
-       " 'emblem': 17,\n",
-       " 'pensacolians': 18,\n",
-       " 'stateside': 19,\n",
-       " 'mouthful': 20,\n",
-       " 'cheezy': 21,\n",
-       " 'retiring': 22,\n",
-       " 'teek': 23,\n",
-       " 'propagandized': 24,\n",
-       " 'trawling': 25,\n",
-       " 'prospers': 26,\n",
-       " 'clowes': 27,\n",
-       " 'evr': 28,\n",
-       " 'milennium': 29,\n",
-       " 'tranquillo': 30,\n",
-       " 'wipe': 31,\n",
-       " 'bogie': 32,\n",
-       " 'hither': 33,\n",
-       " 'camo': 34,\n",
-       " 'reaves': 35,\n",
-       " 'walled': 36,\n",
-       " 'hilcox': 37,\n",
-       " 'squaring': 38,\n",
-       " 'fp': 39,\n",
-       " 'gnashes': 40,\n",
-       " 'lunohod': 41,\n",
-       " 'allocated': 42,\n",
-       " 'bloodsucker': 43,\n",
-       " 'lama': 44,\n",
-       " 'roland': 45,\n",
-       " 'breathed': 46,\n",
-       " 'cucumbers': 47,\n",
-       " 'siam': 48,\n",
-       " 'martineau': 49,\n",
-       " 'phillipine': 50,\n",
-       " 'nominations': 51,\n",
-       " 'hepo': 52,\n",
-       " 'tabatabai': 53,\n",
-       " 'thine': 54,\n",
-       " 'hickland': 55,\n",
-       " 'absurd': 56,\n",
-       " 'scrub': 57,\n",
-       " 'opulent': 58,\n",
-       " 'horus': 59,\n",
-       " 'cundy': 60,\n",
-       " 'servings': 61,\n",
-       " 'baghdad': 62,\n",
-       " 'chandra': 63,\n",
-       " 'bie': 64,\n",
-       " 'lactating': 65,\n",
-       " 'suchet': 66,\n",
-       " 'tangibly': 67,\n",
-       " 'bundy': 68,\n",
-       " 'choirmaster': 69,\n",
-       " 'makepeace': 70,\n",
-       " 'dehavilland': 71,\n",
-       " 'ripiao': 72,\n",
-       " 'kennedys': 73,\n",
-       " 'manoeuvres': 74,\n",
-       " 'olaf': 75,\n",
-       " 'gravy': 76,\n",
-       " 'silicon': 77,\n",
-       " 'luckely': 78,\n",
-       " 'alcaine': 79,\n",
-       " 'karmically': 80,\n",
-       " 'pricing': 81,\n",
-       " 'guiseppe': 82,\n",
-       " 'morganbut': 83,\n",
-       " 'mythologies': 84,\n",
-       " 'tschaikowsky': 85,\n",
-       " 'reliefs': 86,\n",
-       " 'installations': 87,\n",
-       " 'plagued': 88,\n",
-       " 'interference': 89,\n",
-       " 'cinematicism': 90,\n",
-       " 'defininitive': 91,\n",
-       " 'willem': 92,\n",
-       " 'tooo': 93,\n",
-       " 'texas': 94,\n",
-       " 'respected': 95,\n",
-       " 'enables': 96,\n",
-       " 'kickers': 97,\n",
-       " 'beached': 98,\n",
-       " 'inferno': 99,\n",
-       " 'playoffs': 100,\n",
-       " 'lofaso': 101,\n",
-       " 'ministry': 102,\n",
-       " 'appalingly': 103,\n",
-       " 'daviau': 104,\n",
-       " 'adagio': 105,\n",
-       " 'eventless': 106,\n",
-       " 'abandoning': 107,\n",
-       " 'them': 108,\n",
-       " 'commercializing': 109,\n",
-       " 'circuitous': 110,\n",
-       " 'fozzie': 111,\n",
-       " 'lambaste': 112,\n",
-       " 'alicianne': 113,\n",
-       " 'instrument': 114,\n",
-       " 'androids': 115,\n",
-       " 'vahtang': 116,\n",
-       " 'scrapped': 117,\n",
-       " 'msg': 118,\n",
-       " 'overripe': 119,\n",
-       " 'orchestrates': 120,\n",
-       " 'mania': 121,\n",
-       " 'cristian': 122,\n",
-       " 'jackhammered': 123,\n",
-       " 'rehearsal': 124,\n",
-       " 'dm': 125,\n",
-       " 'volunteers': 126,\n",
-       " 'unfeeling': 127,\n",
-       " 'hirsute': 128,\n",
-       " 'frankly': 129,\n",
-       " 'chronically': 130,\n",
-       " 'sociology': 131,\n",
-       " 'dejas': 132,\n",
-       " 'allo': 133,\n",
-       " 'pffeifer': 134,\n",
-       " 'contravert': 135,\n",
-       " 'kidnapper': 136,\n",
-       " 'marissa': 137,\n",
-       " 'maclaughlin': 138,\n",
-       " 'maharashtrian': 139,\n",
-       " 'clothe': 140,\n",
-       " 'impale': 141,\n",
-       " 'spacewalk': 142,\n",
-       " 'cobbs': 143,\n",
-       " 'gonzo': 144,\n",
-       " 'rifles': 145,\n",
-       " 'flinstones': 146,\n",
-       " 'greco': 147,\n",
-       " 'eq': 148,\n",
-       " 'blaming': 149,\n",
-       " 'murdock': 150,\n",
-       " 'blackgood': 151,\n",
-       " 'watanabe': 152,\n",
-       " 'storybooks': 153,\n",
-       " 'bargearse': 154,\n",
-       " 'deservingly': 155,\n",
-       " 'rafe': 156,\n",
-       " 'lillian': 157,\n",
-       " 'cuter': 158,\n",
-       " 'brella': 159,\n",
-       " 'honeycombs': 160,\n",
-       " 'slowmo': 161,\n",
-       " 'chimeric': 162,\n",
-       " 'occupations': 163,\n",
-       " 'watchings': 164,\n",
-       " 'josephs': 165,\n",
-       " 'translation': 166,\n",
-       " 'storyline': 167,\n",
-       " 'sjholm': 168,\n",
-       " 'remade': 169,\n",
-       " 'rusty': 170,\n",
-       " 'angrezon': 171,\n",
-       " 'darlene': 172,\n",
-       " 'possesor': 173,\n",
-       " 'expertise': 174,\n",
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-       " 'offside': 183,\n",
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-       " 'sired': 185,\n",
-       " 'blecher': 186,\n",
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-       " 'commemorated': 193,\n",
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-       " 'deasy': 195,\n",
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-       " 'dik': 220,\n",
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-       " 'tremell': 224,\n",
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-       " 'swordplay': 227,\n",
-       " 'runtime': 228,\n",
-       " 'chevette': 229,\n",
-       " 'covering': 230,\n",
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-       " 'mendezes': 235,\n",
-       " 'indicator': 236,\n",
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-       " 'arrrrgh': 246,\n",
-       " 'urgently': 247,\n",
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-       " 'hardcore': 249,\n",
-       " 'westernized': 250,\n",
-       " 'strangles': 251,\n",
-       " 'bachelorette': 252,\n",
-       " 'litreture': 253,\n",
-       " 'offsprings': 254,\n",
-       " 'crudest': 255,\n",
-       " 'mores': 256,\n",
-       " 'unveiling': 257,\n",
-       " 'bisaya': 258,\n",
-       " 'amalio': 259,\n",
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-       " 'straw': 262,\n",
-       " 'dnd': 263,\n",
-       " 'detailed': 264,\n",
-       " 'bullfrogs': 265,\n",
-       " 'chooses': 266,\n",
-       " 'darko': 267,\n",
-       " 'bearings': 268,\n",
-       " 'squadders': 269,\n",
-       " 'moriarty': 270,\n",
-       " 'intuitive': 271,\n",
-       " 'inculpate': 272,\n",
-       " 'barbaric': 273,\n",
-       " 'ladyhawk': 274,\n",
-       " 'trench': 275,\n",
-       " 'yoshitsune': 276,\n",
-       " 'jinks': 277,\n",
-       " 'reichdeutch': 278,\n",
-       " 'piloting': 279,\n",
-       " 'sherrys': 280,\n",
-       " 'schiller': 281,\n",
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-       " 'wilton': 283,\n",
-       " 'ber': 284,\n",
-       " 'posit': 285,\n",
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-       " 'eleanor': 287,\n",
-       " 'soaring': 288,\n",
-       " 'dirossario': 289,\n",
-       " 'liquidates': 290,\n",
-       " 'syria': 291,\n",
-       " 'abstract': 292,\n",
-       " 'gonorrhea': 293,\n",
-       " 'kolker': 294,\n",
-       " 'steady': 295,\n",
-       " 'ontario': 296,\n",
-       " 'metafiction': 297,\n",
-       " 'thinnes': 298,\n",
-       " 'shart': 299,\n",
-       " 'nishaabd': 300,\n",
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-       " 'intercedes': 302,\n",
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-       " 'flimsiest': 304,\n",
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-       " 'grudging': 307,\n",
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-       " 'hotter': 314,\n",
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-       " 'evolutions': 317,\n",
-       " 'eek': 318,\n",
-       " 'mohawk': 319,\n",
-       " 'wetters': 320,\n",
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-       " 'mongolia': 322,\n",
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-       " 'jembs': 329,\n",
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-       " 'dy': 390,\n",
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-       " 'fuflo': 981,\n",
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-       " 'abounding': 996,\n",
-       " 'infantryman': 997,\n",
-       " 'sumin': 998,\n",
-       " 'kont': 999,\n",
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+       " 'socialite': 242,\n",
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+       " 'isabel': 282,\n",
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+       " 'lineal': 288,\n",
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+       " 'recollecting': 946,\n",
+       " 'tis': 947,\n",
+       " 'existience': 948,\n",
+       " 'creditable': 952,\n",
+       " 'volpe': 950,\n",
+       " 'aid': 951,\n",
+       " 'underwater': 953,\n",
+       " 'bice': 954,\n",
+       " 'completetly': 955,\n",
+       " 'grindingly': 956,\n",
+       " 'ether': 957,\n",
+       " 'dwindling': 958,\n",
+       " 'limping': 3794,\n",
+       " 'insted': 960,\n",
+       " 'corinne': 51447,\n",
+       " 'misinterpreted': 961,\n",
+       " 'valdez': 962,\n",
+       " 'initiation': 963,\n",
+       " 'irreplaceable': 64408,\n",
+       " 'diffident': 964,\n",
+       " 'thanatos': 965,\n",
+       " 'lolly': 966,\n",
+       " 'frogmarched': 968,\n",
+       " 'dictate': 969,\n",
+       " 'concussion': 970,\n",
+       " 'consumers': 971,\n",
+       " 'vaugn': 162,\n",
+       " 'extremly': 973,\n",
+       " 'cahill': 65874,\n",
+       " 'unpleasantness': 68093,\n",
+       " 'verveen': 976,\n",
+       " 'thingamajig': 975,\n",
+       " 'cope': 61887,\n",
+       " 'ludicrously': 12476,\n",
+       " 'unintelligible': 977,\n",
+       " 'orson': 978,\n",
+       " 'goofed': 979,\n",
+       " 'colonize': 980,\n",
+       " 'leaf': 981,\n",
+       " 'vanner': 982,\n",
+       " 'brattiest': 983,\n",
+       " 'enjolras': 17547,\n",
+       " 'parallels': 984,\n",
+       " 'cinemagraphic': 985,\n",
+       " 'vaguest': 987,\n",
+       " 'vca': 990,\n",
+       " 'kiesser': 989,\n",
+       " 'marybeth': 66421,\n",
+       " 'characteriology': 991,\n",
+       " 'squash': 993,\n",
+       " 'rebeecca': 994,\n",
+       " 'mauldin': 995,\n",
+       " 'extender': 997,\n",
+       " 'zeppelins': 61891,\n",
+       " 'zealous': 50965,\n",
+       " 'personality': 998,\n",
+       " 'greatest': 999,\n",
+       " 'creeper': 61895,\n",
+       " 'touring': 1000,\n",
+       " 'shirdan': 1001,\n",
+       " 'meal': 56790,\n",
+       " 'lale': 61894,\n",
+       " 'kalifonia': 1002,\n",
+       " 'neds': 1003,\n",
+       " 'improbable': 1004,\n",
+       " 'offed': 1005,\n",
+       " 'linebacker': 1007,\n",
+       " 'mirror': 1008,\n",
+       " 'comradery': 1009,\n",
+       " 'windmill': 1010,\n",
+       " 'holidays': 37073,\n",
+       " 'option': 1013,\n",
+       " 'dudettes': 1014,\n",
+       " 'amfortas': 1015,\n",
        " ...}"
       ]
      },
@@ -4829,7 +4870,9 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -4858,7 +4901,9 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "def get_target_for_label(label):\n",
@@ -4884,7 +4929,9 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -4904,7 +4951,9 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -4931,7 +4980,9 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -4951,7 +5002,9 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -5271,7 +5324,9 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -5295,7 +5350,9 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -5329,7 +5386,9 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -5364,7 +5423,9 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -5414,7 +5475,9 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -5456,7 +5519,9 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -5500,6 +5565,7 @@
    "cell_type": "code",
    "execution_count": 43,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -5876,6 +5942,7 @@
    "cell_type": "code",
    "execution_count": 45,
    "metadata": {
+    "collapsed": false,
     "scrolled": true
    },
    "outputs": [
@@ -5905,7 +5972,9 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -5916,7 +5985,6 @@
     }
    ],
    "source": [
-    "# evaluate our model before training (just to show how horrible it is)\n",
     "mlp.test(reviews[-1000:],labels[-1000:])"
    ]
   },
@@ -5932,7 +6000,9 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -5964,7 +6034,9 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -5996,7 +6068,9 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -6027,7 +6101,9 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -6081,7 +6157,9 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -6101,7 +6179,9 @@
   {
    "cell_type": "code",
    "execution_count": 58,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -6145,7 +6225,9 @@
   {
    "cell_type": "code",
    "execution_count": 61,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -6454,7 +6536,9 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -6489,7 +6573,9 @@
   {
    "cell_type": "code",
    "execution_count": 64,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -7515,7 +7601,9 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -7536,7 +7624,9 @@
   {
    "cell_type": "code",
    "execution_count": 66,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -8557,7 +8647,9 @@
   {
    "cell_type": "code",
    "execution_count": 67,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -8607,7 +8699,9 @@
   {
    "cell_type": "code",
    "execution_count": 68,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -8775,7 +8869,9 @@
   {
    "cell_type": "code",
    "execution_count": 69,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -8954,7 +9050,9 @@
   {
    "cell_type": "code",
    "execution_count": 71,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -9451,7 +9549,9 @@
   {
    "cell_type": "code",
    "execution_count": 73,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -9486,7 +9586,9 @@
   {
    "cell_type": "code",
    "execution_count": 74,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -10510,7 +10612,9 @@
   {
    "cell_type": "code",
    "execution_count": 75,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -10545,7 +10649,9 @@
   {
    "cell_type": "code",
    "execution_count": 76,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -11571,7 +11677,9 @@
   {
    "cell_type": "code",
    "execution_count": 77,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "mlp_full = SentimentNetwork(reviews[:-1000],labels[:-1000],min_count=0,polarity_cutoff=0,learning_rate=0.01)"
@@ -11580,7 +11688,9 @@
   {
    "cell_type": "code",
    "execution_count": 78,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -11607,7 +11717,9 @@
   {
    "cell_type": "code",
    "execution_count": 79,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -11645,1011 +11757,1013 @@
   {
    "cell_type": "code",
    "execution_count": 81,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[('excellent', 0.13672950757352467),\n",
-       " ('perfect', 0.12548286087225943),\n",
-       " ('amazing', 0.091827633925999672),\n",
-       " ('today', 0.090223662694414203),\n",
-       " ('wonderful', 0.089355976962214603),\n",
+       "[('excellent', 0.1367295075735247),\n",
+       " ('perfect', 0.12548286087225946),\n",
+       " ('amazing', 0.091827633925999685),\n",
+       " ('today', 0.090223662694414244),\n",
+       " ('wonderful', 0.089355976962214576),\n",
        " ('fun', 0.08750446667420686),\n",
-       " ('great', 0.087141758882292059),\n",
-       " ('best', 0.085810885617880639),\n",
-       " ('liked', 0.077697629123843398),\n",
-       " ('definitely', 0.076628781406965968),\n",
-       " ('brilliant', 0.073423858769278996),\n",
-       " ('loved', 0.073285428928122134),\n",
-       " ('favorite', 0.072781136036160737),\n",
+       " ('great', 0.087141758882292031),\n",
+       " ('best', 0.085810885617880611),\n",
+       " ('liked', 0.077697629123843412),\n",
+       " ('definitely', 0.076628781406966037),\n",
+       " ('brilliant', 0.073423858769279024),\n",
+       " ('loved', 0.073285428928122162),\n",
+       " ('favorite', 0.072781136036160765),\n",
        " ('superb', 0.071736207178505054),\n",
-       " ('fantastic', 0.070922191916266183),\n",
-       " ('job', 0.069160617207634029),\n",
-       " ('incredible', 0.066424077952614416),\n",
-       " ('enjoyable', 0.065632560502888765),\n",
+       " ('fantastic', 0.070922191916266197),\n",
+       " ('job', 0.06916061720763407),\n",
+       " ('incredible', 0.066424077952614388),\n",
+       " ('enjoyable', 0.06563256050288882),\n",
        " ('rare', 0.064819212662615075),\n",
-       " ('highly', 0.063889453350970529),\n",
-       " ('enjoyed', 0.062127546101812925),\n",
-       " ('wonderfully', 0.062055178604090155),\n",
+       " ('highly', 0.063889453350970515),\n",
+       " ('enjoyed', 0.062127546101812953),\n",
+       " ('wonderfully', 0.062055178604090148),\n",
        " ('perfectly', 0.06109320881188738),\n",
-       " ('fascinating', 0.060663547937493838),\n",
-       " ('bit', 0.059655427045653027),\n",
-       " ('gem', 0.059510859296156793),\n",
-       " ('outstanding', 0.058860808147082999),\n",
-       " ('beautiful', 0.058613934703162049),\n",
-       " ('surprised', 0.058273314482562961),\n",
-       " ('worth', 0.057657484236471192),\n",
-       " ('especially', 0.057422020781760771),\n",
-       " ('refreshing', 0.057310532092265741),\n",
-       " ('entertaining', 0.05661203383562919),\n",
-       " ('hilarious', 0.056168541032286634),\n",
-       " ('masterpiece', 0.054993988649431551),\n",
-       " ('simple', 0.054484083134924068),\n",
-       " ('subtle', 0.054368883033508626),\n",
-       " ('funniest', 0.05345716487130267),\n",
+       " ('fascinating', 0.060663547937493865),\n",
+       " ('bit', 0.059655427045653062),\n",
+       " ('gem', 0.059510859296156786),\n",
+       " ('outstanding', 0.058860808147083006),\n",
+       " ('beautiful', 0.058613934703162091),\n",
+       " ('surprised', 0.058273314482562968),\n",
+       " ('worth', 0.057657484236471213),\n",
+       " ('especially', 0.057422020781760785),\n",
+       " ('refreshing', 0.057310532092265755),\n",
+       " ('entertaining', 0.056612033835629204),\n",
+       " ('hilarious', 0.056168541032286662),\n",
+       " ('masterpiece', 0.054993988649431572),\n",
+       " ('simple', 0.054484083134924088),\n",
+       " ('subtle', 0.054368883033508633),\n",
+       " ('funniest', 0.053457164871302684),\n",
        " ('solid', 0.052903564743620651),\n",
-       " ('awesome', 0.052489194202770387),\n",
-       " ('always', 0.052260328525345283),\n",
-       " ('noir', 0.05153019472640688),\n",
-       " ('guys', 0.051109413645642685),\n",
-       " ('sweet', 0.050818930317526004),\n",
-       " ('unique', 0.050670162263589155),\n",
-       " ('very', 0.050132994948528471),\n",
-       " ('heart', 0.049948058498243596),\n",
+       " ('awesome', 0.052489194202770408),\n",
+       " ('always', 0.052260328525345297),\n",
+       " ('noir', 0.051530194726406894),\n",
+       " ('guys', 0.051109413645642691),\n",
+       " ('sweet', 0.05081893031752599),\n",
+       " ('unique', 0.05067016226358919),\n",
+       " ('very', 0.050132994948528513),\n",
+       " ('heart', 0.049948058498243603),\n",
        " ('moving', 0.049424601164379113),\n",
        " ('atmosphere', 0.048842500895912855),\n",
-       " ('strong', 0.048570880631759218),\n",
-       " ('remember', 0.048479036942291276),\n",
-       " ('believable', 0.048415384391603762),\n",
-       " ('shows', 0.048336045608039571),\n",
-       " ('love', 0.047310648160924645),\n",
-       " ('beautifully', 0.047118717440814875),\n",
-       " ('both', 0.046957278901480305),\n",
-       " ('terrific', 0.046686597975756611),\n",
-       " ('touching', 0.046589962377280948),\n",
-       " ('fine', 0.04625643132885577),\n",
-       " ('caught', 0.046163326224782329),\n",
-       " ('recommended', 0.045876341160885292),\n",
+       " ('strong', 0.048570880631759204),\n",
+       " ('remember', 0.048479036942291262),\n",
+       " ('believable', 0.048415384391603783),\n",
+       " ('shows', 0.048336045608039585),\n",
+       " ('love', 0.047310648160924659),\n",
+       " ('beautifully', 0.047118717440814903),\n",
+       " ('both', 0.046957278901480347),\n",
+       " ('terrific', 0.046686597975756632),\n",
+       " ('touching', 0.046589962377280962),\n",
+       " ('fine', 0.046256431328855756),\n",
+       " ('caught', 0.04616332622478235),\n",
+       " ('recommended', 0.045876341160885278),\n",
        " ('jack', 0.045352909975188323),\n",
-       " ('everyone', 0.045145273964599386),\n",
-       " ('episodes', 0.045064457062621271),\n",
-       " ('classic', 0.044985816637932732),\n",
-       " ('will', 0.044966672557930486),\n",
-       " ('appreciate', 0.044764139584570865),\n",
+       " ('everyone', 0.0451452739645994),\n",
+       " ('episodes', 0.045064457062621285),\n",
+       " ('classic', 0.044985816637932746),\n",
+       " ('will', 0.044966672557930465),\n",
+       " ('appreciate', 0.044764139584570851),\n",
        " ('powerful', 0.044176442621852774),\n",
-       " ('realistic', 0.043597482283464786),\n",
-       " ('performances', 0.043020249087841737),\n",
+       " ('realistic', 0.043597482283464814),\n",
+       " ('performances', 0.04302024908784173),\n",
        " ('human', 0.042657925475092548),\n",
        " ('expecting', 0.042588442995212208),\n",
-       " ('each', 0.042163774519666956),\n",
-       " ('delightful', 0.041815007170235508),\n",
-       " ('cry', 0.041750968395934812),\n",
-       " ('enjoy', 0.041660091797818086),\n",
+       " ('each', 0.042163774519666943),\n",
+       " ('delightful', 0.041815007170235501),\n",
+       " ('cry', 0.041750968395934833),\n",
+       " ('enjoy', 0.041660091797818093),\n",
        " ('you', 0.041465994778271079),\n",
        " ('surprisingly', 0.041393139256517386),\n",
-       " ('think', 0.041103720571057038),\n",
-       " ('performance', 0.040844259420896839),\n",
-       " ('nice', 0.040016506666931732),\n",
-       " ('paced', 0.03994448864759962),\n",
-       " ('true', 0.039750592643370664),\n",
-       " ('tight', 0.039425438825552633),\n",
-       " ('similar', 0.039222380170683496),\n",
-       " ('friendship', 0.039110112764204286),\n",
-       " ('somewhat', 0.03906961573101024),\n",
-       " ('beauty', 0.03813092255473878),\n",
-       " ('short', 0.03798170013140921),\n",
-       " ('life', 0.037716639265310235),\n",
-       " ('stunning', 0.037507364832543751),\n",
-       " ('still', 0.037479827910101494),\n",
-       " ('normal', 0.037422144669435102),\n",
+       " ('think', 0.041103720571057073),\n",
+       " ('performance', 0.040844259420896853),\n",
+       " ('nice', 0.04001650666693176),\n",
+       " ('paced', 0.039944488647599627),\n",
+       " ('true', 0.039750592643370677),\n",
+       " ('tight', 0.039425438825552647),\n",
+       " ('similar', 0.039222380170683489),\n",
+       " ('friendship', 0.039110112764204306),\n",
+       " ('somewhat', 0.039069615731010261),\n",
+       " ('beauty', 0.038130922554738794),\n",
+       " ('short', 0.037981700131409203),\n",
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        " ('kong', 0.012999080313300517),\n",
        " ('mayor', 0.012994758409723568),\n",
-       " ('punishment', 0.012988264949614947),\n",
-       " ('morris', 0.012983710119604966),\n",
-       " ('hall', 0.012981593609354821),\n",
-       " ('match', 0.012980233583057322),\n",
-       " ('bleak', 0.012972505086304056),\n",
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        " ('lindy', 0.012972248933121261),\n",
-       " ('sequence', 0.012964435808713556),\n",
-       " ('learn', 0.012938848970083339),\n",
-       " ('happen', 0.012932836387873745),\n",
-       " ('john', 0.012929524979001662),\n",
-       " ('gothic', 0.012926957011734882),\n",
-       " ('wider', 0.012920985981480958),\n",
-       " ('popular', 0.012891690509844065),\n",
-       " ('diverse', 0.012875263936567809),\n",
-       " ('compare', 0.012869395292065183),\n",
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        " ('brooklyn', 0.01285298624326393),\n",
-       " ('broadcast', 0.012839574692097613),\n",
-       " ('zane', 0.012834302957709142),\n",
-       " ('andrew', 0.01282402094061526),\n",
-       " ('finely', 0.012822716004015853),\n",
-       " ('confronted', 0.012817523686608627),\n",
-       " ('going', 0.01280976283930498),\n",
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        " ('likewise', 0.012804639349082518),\n",
-       " ('breath', 0.012790132659417907),\n",
-       " ('building', 0.012789809704793872),\n",
-       " ('suggesting', 0.012780624321169333),\n",
-       " ('contemporary', 0.012772749462937509),\n",
-       " ('midnight', 0.012766963563112067),\n",
-       " ('victoria', 0.012756422131580529),\n",
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        " ('lasting', 0.012752424415642586),\n",
        " ('kitty', 0.012751468371946007),\n",
-       " ('continued', 0.012744325456485399),\n",
-       " ('indian', 0.012712962842718688),\n",
-       " ('subplots', 0.012709887814283907),\n",
-       " ('douglas', 0.012693830679455891),\n",
-       " ('explosions', 0.012692697593201843),\n",
-       " ('bond', 0.012689802823687819),\n",
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        " ('delightfully', 0.012669417460922622),\n",
-       " ('understated', 0.012669374312789347),\n",
-       " ('greater', 0.012664580396020159),\n",
-       " ('sailing', 0.012662424581282427),\n",
-       " ('images', 0.012661803048859877),\n",
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+       " ('images', 0.01266180304885987),\n",
        " ('copy', 0.012624649645734161),\n",
-       " ('seat', 0.012610464273152516),\n",
-       " ('eleven', 0.012602533659978885),\n",
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        " ('riveting', 0.012591829460094517),\n",
-       " ('boiled', 0.012588863529638755),\n",
-       " ('academy', 0.012581996178142978),\n",
-       " ('whilst', 0.01256984165329564),\n",
-       " ('heaven', 0.012547361621330929),\n",
-       " ('fruit', 0.012543513029693252),\n",
-       " ('reviewer', 0.012534273375083893),\n",
-       " ('cost', 0.012529643005796608),\n",
-       " ('week', 0.012522845015008277),\n",
-       " ('intriguing', 0.012508687653306367),\n",
-       " ('streak', 0.012507752385208555),\n",
-       " ('san', 0.012502130058217917),\n",
-       " ('awareness', 0.012476446442012448),\n",
-       " ('catching', 0.012467108595451533),\n",
-       " ('kicks', 0.012457714930570582),\n",
-       " ('complexities', 0.012454362663082459),\n",
-       " ('draws', 0.012447753285125903),\n",
-       " ('easily', 0.012444885855614886),\n",
-       " ('ealing', 0.012444339255708927),\n",
-       " ('psychopath', 0.012431259926282275),\n",
-       " ('skin', 0.01242424854097357),\n",
-       " ('creative', 0.012386713452491531),\n",
-       " ('recognition', 0.012354025801439425),\n",
-       " ('downey', 0.012348698765161136),\n",
-       " ('symbolism', 0.012329925038271329),\n",
-       " ('touches', 0.01232801347075145),\n",
+       " ('boiled', 0.012588863529638759),\n",
+       " ('academy', 0.012581996178142974),\n",
+       " ('whilst', 0.012569841653295642),\n",
+       " ('heaven', 0.012547361621330914),\n",
+       " ('fruit', 0.012543513029693249),\n",
+       " ('reviewer', 0.012534273375083886),\n",
+       " ('cost', 0.012529643005796615),\n",
+       " ('week', 0.012522845015008281),\n",
+       " ('intriguing', 0.012508687653306356),\n",
+       " ('streak', 0.012507752385208562),\n",
+       " ('san', 0.012502130058217934),\n",
+       " ('awareness', 0.012476446442012451),\n",
+       " ('catching', 0.012467108595451522),\n",
+       " ('kicks', 0.012457714930570581),\n",
+       " ('complexities', 0.012454362663082464),\n",
+       " ('draws', 0.012447753285125917),\n",
+       " ('easily', 0.012444885855614875),\n",
+       " ('ealing', 0.012444339255708925),\n",
+       " ('psychopath', 0.012431259926282268),\n",
+       " ('skin', 0.012424248540973577),\n",
+       " ('creative', 0.012386713452491529),\n",
+       " ('recognition', 0.012354025801439416),\n",
+       " ('downey', 0.012348698765161131),\n",
+       " ('symbolism', 0.012329925038271331),\n",
+       " ('touches', 0.01232801347075147),\n",
        " ('everyday', 0.012324934809895893),\n",
-       " ('achieves', 0.012314898707483488),\n",
-       " ('outcast', 0.012313662230219676),\n",
-       " ('overwhelmed', 0.012306633138869476),\n",
+       " ('achieves', 0.012314898707483495),\n",
+       " ('outcast', 0.012313662230219678),\n",
+       " ('overwhelmed', 0.012306633138869474),\n",
        " ...]"
       ]
      },
@@ -12665,1011 +12779,1013 @@
   {
    "cell_type": "code",
    "execution_count": 82,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "[('worst', 0.16966107259049848),\n",
        " ('awful', 0.12026847019691246),\n",
-       " ('waste', 0.11945367265311005),\n",
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        " ('poor', 0.092758887574435497),\n",
-       " ('terrible', 0.091425387197727942),\n",
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        " ('dull', 0.084209271678223618),\n",
-       " ('poorly', 0.081241544516042055),\n",
-       " ('disappointment', 0.080064759621368733),\n",
-       " ('fails', 0.078599773723337513),\n",
-       " ('disappointing', 0.077339485480323378),\n",
-       " ('boring', 0.077127858748012909),\n",
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        " ('unfortunately', 0.075502449705859079),\n",
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-       " ('mess', 0.070564299623590399),\n",
-       " ('stupid', 0.069484822832543022),\n",
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-       " ('minutes', 0.049784532804242172),\n",
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-       " ('ludicrous', 0.034159649323816037),\n",
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-       " ('nudity', 0.028662654953266066),\n",
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        " ('apparently', 0.028291626941517923),\n",
-       " ('zombies', 0.028178583120430679),\n",
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        " ('sense', 0.028166740534758778),\n",
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-       " ('israeli', 0.0094750077183364707),\n",
-       " ('failing', 0.0094711841313976936),\n",
-       " ('paying', 0.0094692344066851317),\n",
-       " ('godzilla', 0.009458691554843782),\n",
-       " ('dumber', 0.0094582903092924886),\n",
-       " ('earn', 0.0094476224928424987),\n",
-       " ('slows', 0.009446746387248758),\n",
-       " ('held', 0.009445273681791478),\n",
-       " ('chase', 0.0094438362611946429),\n",
+       " ('plots', 0.0095225805490624735),\n",
+       " ('danger', 0.0095171205654693055),\n",
+       " ('costumes', 0.0094980144667524517),\n",
+       " ('evidently', 0.0094952158467012243),\n",
+       " ('minus', 0.0094911495174661246),\n",
+       " ('reporters', 0.009483681104099086),\n",
+       " ('israeli', 0.0094750077183364655),\n",
+       " ('failing', 0.0094711841313976971),\n",
+       " ('paying', 0.00946923440668513),\n",
+       " ('godzilla', 0.0094586915548437837),\n",
+       " ('dumber', 0.0094582903092924851),\n",
+       " ('earn', 0.0094476224928425039),\n",
+       " ('slows', 0.0094467463872487598),\n",
+       " ('held', 0.0094452736817914867),\n",
+       " ('chase', 0.0094438362611946377),\n",
        " ('lies', 0.0094383969845033416),\n",
-       " ('hands', 0.0094381781614589211),\n",
-       " ('grief', 0.0094238494534102882),\n",
+       " ('hands', 0.0094381781614589176),\n",
+       " ('grief', 0.00942384945341029),\n",
        " ('brains', 0.0094182153416632122),\n",
-       " ('tom', 0.0094130433384347224),\n",
-       " ('resurrected', 0.009408342343729054),\n",
-       " ('asking', 0.0094021029403453318),\n",
-       " ('sleeps', 0.0094017951882658258),\n",
-       " ('porno', 0.0093907201413965091),\n",
-       " ('somehow', 0.0093889261270860436),\n",
-       " ('sarcasm', 0.0093886064393904154),\n",
-       " ('tie', 0.0093856009366311589),\n",
-       " ('fall', 0.0093801640008931205),\n",
-       " ('bring', 0.009379127354576142),\n",
-       " ('rape', 0.0093760851230746574),\n",
-       " ('village', 0.0093684513318614028),\n",
-       " ('kitchen', 0.0093649071460109555),\n",
-       " ('concerned', 0.0093611353238811316),\n",
-       " ('republic', 0.0093499426948764203),\n",
-       " ('hell', 0.0093400360705317102),\n",
-       " ('inducing', 0.0093382129792553524),\n",
-       " ('stomach', 0.0093378286385158542),\n",
-       " ('shambles', 0.0093335457329829785),\n",
+       " ('tom', 0.009413043338434738),\n",
+       " ('resurrected', 0.0094083423437290557),\n",
+       " ('asking', 0.0094021029403453284),\n",
+       " ('sleeps', 0.0094017951882658275),\n",
+       " ('porno', 0.0093907201413965073),\n",
+       " ('somehow', 0.0093889261270860523),\n",
+       " ('sarcasm', 0.0093886064393904119),\n",
+       " ('tie', 0.0093856009366311537),\n",
+       " ('fall', 0.0093801640008931257),\n",
+       " ('bring', 0.0093791273545761489),\n",
+       " ('rape', 0.0093760851230746418),\n",
+       " ('village', 0.0093684513318614097),\n",
+       " ('kitchen', 0.0093649071460109538),\n",
+       " ('concerned', 0.0093611353238811489),\n",
+       " ('republic', 0.0093499426948764237),\n",
+       " ('hell', 0.0093400360705317223),\n",
+       " ('inducing', 0.0093382129792553593),\n",
+       " ('stomach', 0.009337828638515849),\n",
+       " ('shambles', 0.009333545732982982),\n",
        " ('virgin', 0.0093312001339055945),\n",
-       " ('extraneous', 0.0093250413800351328),\n",
-       " ('cameras', 0.0093229460267977207),\n",
-       " ('suffers', 0.0093204929924829965),\n",
-       " ('justified', 0.0093163217479363195),\n",
-       " ('plummer', 0.009294827328510398),\n",
-       " ('ponderous', 0.0092880344237223356),\n",
-       " ('player', 0.0092802296345443763),\n",
-       " ('survivor', 0.0092767026472125799),\n",
-       " ('rainy', 0.0092697034218137495),\n",
-       " ('graces', 0.0092620944963291325),\n",
+       " ('extraneous', 0.009325041380035138),\n",
+       " ('cameras', 0.0093229460267977189),\n",
+       " ('suffers', 0.0093204929924830034),\n",
+       " ('justified', 0.009316321747936309),\n",
+       " ('plummer', 0.0092948273285103945),\n",
+       " ('ponderous', 0.0092880344237223321),\n",
+       " ('player', 0.0092802296345443781),\n",
+       " ('survivor', 0.0092767026472125765),\n",
+       " ('rainy', 0.0092697034218137461),\n",
+       " ('graces', 0.0092620944963291273),\n",
        " ...]"
       ]
      },
@@ -13685,7 +13801,9 @@
   {
    "cell_type": "code",
    "execution_count": 83,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import matplotlib.colors as colors\n",
@@ -13728,7 +13846,9 @@
   {
    "cell_type": "code",
    "execution_count": 85,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from sklearn.manifold import TSNE\n",
@@ -13739,7 +13859,9 @@
   {
    "cell_type": "code",
    "execution_count": 87,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -13944,7 +14066,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [default]",
    "language": "python",
    "name": "python3"
   },
@@ -13958,7 +14080,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.3"
+   "version": "3.5.2"
   }
  },
  "nbformat": 4,