Changes to jupyter notebook for lightning talks

edX Lightning Talk.ipynb

@@ -212,42 +212,14 @@
     "\n",
     "We can partition by threes too:\n",
     "\n",
-    "(<span style=\"color:blue\">The</span> <span style=\"color:red\">quick brown</span>) (quick brown fox) ... (<span style=\"color:blue\">the</span> <span style=\"color:red\">lazy dog</span>)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "fragment"
-    }
-   },
-   "source": [
+    "(<span style=\"color:blue\">The</span> <span style=\"color:red\">quick brown</span>) (quick brown fox) ... (<span style=\"color:blue\">the</span> <span style=\"color:red\">lazy dog</span>)\n",
+    "\n",
     "Or, the condition can be two words (`condition = 'the lazy'`):\n",
     "\n",
-    "(The quick brown) (quick brown fox) ... (<span style=\"color:blue\">the lazy</span> <span span=\"color:red\">dog</span>)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "fragment"
-    }
-   },
-   "source": [
+    "(The quick brown) (quick brown fox) ... (<span style=\"color:blue\">the lazy</span> <span style=\"color:red\">dog</span>)\n",
+    "\n",
+    "These are **trigrams**.\n",
     "\n",
-    "These are **trigrams**."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "fragment"
-    }
-   },
-   "source": [
     "We can partition any **N** number of words together as **ngrams**."
    ]
   },
@@ -343,7 +315,7 @@
    "source": [
     "words = ('The quick brown fox jumped over the '\n",
     "        'lazy dog and the quick cat').split(' ')\n",
-    "print words"
+    "print(words)"
    ]
   },
   {
@@ -409,6 +381,17 @@
     "{k: dict(v) for k, v in dict(cfd).items()}"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "## Conditional Frequency Distributions (CFDs) ##"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -501,9 +484,9 @@
     "word = random.choice(TEXT)\n",
     "# generate 15 more words\n",
     "for i in range(15):\n",
-    "    print word,\n",
+    "    print(word + ' ', end='')\n",
     "    if word in cfd:\n",
-    "        word = random.choice(cfd[word].keys())\n",
+    "        word = random.choice(list(cfd[word].keys()))\n",
     "    else:\n",
     "        break"
    ]
@@ -604,10 +587,12 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "fragment"
+     "slide_type": "slide"
     }
    },
    "source": [
+    "# Syllables\n",
+    "\n",
     "* poet: /ˈpoʊət/\n",
     "* does: /ˈdʌz/\n",
     "\n",
@@ -806,7 +791,7 @@
    "source": [
     "from stat_parser import Parser\n",
     "parsed = Parser().parse('The quick brown fox jumps over the lazy dog.')\n",
-    "print parsed"
+    "print(parsed)"
    ]
   },
   {
@@ -917,6 +902,18 @@
     "[https://spacy.io/docs/api/#speed-comparison](https://spacy.io/docs/api/#speed-comparison)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "![Screenshot of displaCy, a dependency visualizer for spaCy](images/displacy.png)\n",
+    "[https://demos.explosion.ai/displacy/](https://demos.explosion.ai/displacy/)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -962,6 +959,20 @@
     "[http://karpathy.github.io/2015/05/21/rnn-effectiveness/](http://karpathy.github.io/2015/05/21/rnn-effectiveness/)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "![Screenshot of word-rnn readme on Github](images/word-rnn.png)\n",
+    "[word-rnn](https://github.com/larspars/word-rnn)\n",
+    "\n",
+    "[word-rnn-tensorflow](https://github.com/hunkim/word-rnn-tensorflow)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -973,28 +984,30 @@
    "source": [
     "# The end #\n",
     "\n",
-    "Questions?"
+    "Questions?\n",
+    "\n",
+    "Full write up at: [hallada.net/blog](http://www.hallada.net/2017/07/11/generating-random-poems-with-python.html)"
    ]
   }
  ],
  "metadata": {
   "celltoolbar": "Slideshow",
   "kernelspec": {
-   "display_name": "Python 2",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "python2"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.12"
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
   },
   "livereveal": {
    "scroll": true,