diff --git a/lectures/lec01/Introduction.ipynb b/lectures/lec01/Introduction.ipynb index c4c098b..fb139ed 100644 --- a/lectures/lec01/Introduction.ipynb +++ b/lectures/lec01/Introduction.ipynb @@ -110,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 70, "metadata": { "collapsed": false, "slideshow": { @@ -139,19 +139,32 @@ " return [doc for doc in documents if doc == query]\n", "\n", "\n", - "\n" + "def search2(documents, query):\n", + " results = []\n", + " for doc in documents:\n", + " if doc == query:\n", + " results.append(doc)\n", + " return results\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 71, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['cat', 'cat']\n" + ] + } + ], "source": [ "print(search(documents, 'cat'))\n", "\n", @@ -194,7 +207,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 72, "metadata": { "collapsed": false }, @@ -208,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 73, "metadata": { "collapsed": true, "slideshow": { @@ -226,14 +239,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 74, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[['dog', 'cat'], ['cat', 'zebra']]\n" + ] + } + ], "source": [ "print(search(documents, 'cat'))\n", "\n", @@ -280,7 +301,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 75, "metadata": { "collapsed": true, "slideshow": { @@ -303,11 +324,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 76, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 2]\n" + ] + } + ], "source": [ "print(index['dog'])\n", "\n", @@ -317,11 +346,60 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 77, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "['__class__',\n", + " '__contains__',\n", + " '__delattr__',\n", + " '__delitem__',\n", + " '__dir__',\n", + " '__doc__',\n", + " '__eq__',\n", + " '__format__',\n", + " '__ge__',\n", + " '__getattribute__',\n", + " '__getitem__',\n", + " '__gt__',\n", + " '__hash__',\n", + " '__init__',\n", + " '__iter__',\n", + " '__le__',\n", + " '__len__',\n", + " '__lt__',\n", + " '__ne__',\n", + " '__new__',\n", + " '__reduce__',\n", + " '__reduce_ex__',\n", + " '__repr__',\n", + " '__setattr__',\n", + " '__setitem__',\n", + " '__sizeof__',\n", + " '__str__',\n", + " '__subclasshook__',\n", + " 'clear',\n", + " 'copy',\n", + " 'fromkeys',\n", + " 'get',\n", + " 'items',\n", + " 'keys',\n", + " 'pop',\n", + " 'popitem',\n", + " 'setdefault',\n", + " 'update',\n", + " 'values']" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Python tip: dir() will list all attributes/methods of a variable.\n", "dir(index)\n", @@ -332,11 +410,127 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 78, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on dict object:\n", + "\n", + "class dict(object)\n", + " | dict() -> new empty dictionary\n", + " | dict(mapping) -> new dictionary initialized from a mapping object's\n", + " | (key, value) pairs\n", + " | dict(iterable) -> new dictionary initialized as if via:\n", + " | d = {}\n", + " | for k, v in iterable:\n", + " | d[k] = v\n", + " | dict(**kwargs) -> new dictionary initialized with the name=value pairs\n", + " | in the keyword argument list. For example: dict(one=1, two=2)\n", + " | \n", + " | Methods defined here:\n", + " | \n", + " | __contains__(self, key, /)\n", + " | True if D has a key k, else False.\n", + " | \n", + " | __delitem__(self, key, /)\n", + " | Delete self[key].\n", + " | \n", + " | __eq__(self, value, /)\n", + " | Return self==value.\n", + " | \n", + " | __ge__(self, value, /)\n", + " | Return self>=value.\n", + " | \n", + " | __getattribute__(self, name, /)\n", + " | Return getattr(self, name).\n", + " | \n", + " | __getitem__(...)\n", + " | x.__getitem__(y) <==> x[y]\n", + " | \n", + " | __gt__(self, value, /)\n", + " | Return self>value.\n", + " | \n", + " | __init__(self, /, *args, **kwargs)\n", + " | Initialize self. See help(type(self)) for accurate signature.\n", + " | \n", + " | __iter__(self, /)\n", + " | Implement iter(self).\n", + " | \n", + " | __le__(self, value, /)\n", + " | Return self<=value.\n", + " | \n", + " | __len__(self, /)\n", + " | Return len(self).\n", + " | \n", + " | __lt__(self, value, /)\n", + " | Return self size of D in memory, in bytes\n", + " | \n", + " | clear(...)\n", + " | D.clear() -> None. Remove all items from D.\n", + " | \n", + " | copy(...)\n", + " | D.copy() -> a shallow copy of D\n", + " | \n", + " | fromkeys(iterable, value=None, /) from builtins.type\n", + " | Returns a new dict with keys from iterable and values equal to value.\n", + " | \n", + " | get(...)\n", + " | D.get(k[,d]) -> D[k] if k in D, else d. d defaults to None.\n", + " | \n", + " | items(...)\n", + " | D.items() -> a set-like object providing a view on D's items\n", + " | \n", + " | keys(...)\n", + " | D.keys() -> a set-like object providing a view on D's keys\n", + " | \n", + " | pop(...)\n", + " | D.pop(k[,d]) -> v, remove specified key and return the corresponding value.\n", + " | If key is not found, d is returned if given, otherwise KeyError is raised\n", + " | \n", + " | popitem(...)\n", + " | D.popitem() -> (k, v), remove and return some (key, value) pair as a\n", + " | 2-tuple; but raise KeyError if D is empty.\n", + " | \n", + " | setdefault(...)\n", + " | D.setdefault(k[,d]) -> D.get(k,d), also set D[k]=d if k not in D\n", + " | \n", + " | update(...)\n", + " | D.update([E, ]**F) -> None. Update D from dict/iterable E and F.\n", + " | If E is present and has a .keys() method, then does: for k in E: D[k] = E[k]\n", + " | If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v\n", + " | In either case, this is followed by: for k in F: D[k] = F[k]\n", + " | \n", + " | values(...)\n", + " | D.values() -> an object providing a view on D's values\n", + " | \n", + " | ----------------------------------------------------------------------\n", + " | Data and other attributes defined here:\n", + " | \n", + " | __hash__ = None\n", + "\n" + ] + } + ], "source": [ "# Python tip: help() will list\n", "# documentation for variable/method.\n", @@ -360,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 79, "metadata": { "collapsed": true, "slideshow": { @@ -378,14 +572,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 80, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[['dog', 'cat'], ['cat', 'zebra']]\n" + ] + } + ], "source": [ "print(indexed_search(documents, index, 'cat'))\n", "\n", @@ -454,7 +656,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 81, "metadata": { "collapsed": true, "slideshow": { @@ -475,14 +677,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 82, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[['dog', 'cat']]\n" + ] + } + ], "source": [ "print(and_search(documents, index, ['cat', 'dog']))\n", "\n", @@ -596,14 +806,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 83, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "['Timestamp',\n", + " 'First Name',\n", + " 'Last Name',\n", + " 'IIT Email Address',\n", + " 'CWID (A#)',\n", + " \"GitHub Username (Please create a new account at http://github.com if you don't already have one.)\",\n", + " 'How familiar are you with version control? (git, svn, mercurial, cvs, etc.)',\n", + " 'How familiar are you with Python?',\n", + " 'Have you taken a course on Machine Learning or Data Mining?',\n", + " 'Why are you taking this course?']" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# survey.txt contains tab-separated survey results.\n", "survey = [line.strip().split('\\t') for line in open('survey.txt')]\n", @@ -615,7 +845,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 84, "metadata": { "collapsed": false }, @@ -643,11 +873,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 85, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plot_results_for_column(survey, 8)\n", "\n", @@ -685,11 +948,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 88, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[('to', 54),\n", + " ('and', 42),\n", + " ('i', 37),\n", + " ('in', 25),\n", + " ('learn', 21),\n", + " ('it', 18),\n", + " ('the', 17),\n", + " ('my', 17),\n", + " ('about', 15),\n", + " ('search', 15),\n", + " ('data', 14),\n", + " ('this', 14),\n", + " ('a', 12),\n", + " ('like', 12),\n", + " ('interesting', 12),\n", + " ('of', 12),\n", + " ('interested', 11),\n", + " ('want', 11),\n", + " ('is', 10),\n", + " ('retrieval', 10)]" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Count terms in responses to \"Why are you taking this course?\"\n", "term_counts = Counter()\n", @@ -703,11 +996,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 89, "metadata": { "collapsed": false }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[(('to', 'learn'), 19),\n", + " (('want', 'to'), 11),\n", + " (('interested', 'in'), 10),\n", + " (('learn', 'about'), 8),\n", + " (('search', 'engine'), 8),\n", + " (('information', 'retrieval'), 6),\n", + " (('like', 'to'), 6),\n", + " (('i', 'want'), 6),\n", + " (('learn', 'more'), 5),\n", + " (('data', 'mining'), 5),\n", + " (('i', 'am'), 5),\n", + " (('this', 'course'), 5),\n", + " (('in', 'the'), 4),\n", + " (('i', 'would'), 4),\n", + " (('to', 'take'), 4),\n", + " (('in', 'my'), 4),\n", + " (('would', 'like'), 4),\n", + " (('about', 'data'), 4),\n", + " (('more', 'about'), 4),\n", + " (('and', 'i'), 4)]" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Count 2-word phrases (bigrams) in responses to \"Why are you taking this course?\"\n", "term_counts = Counter()\n",