Project2 - Recommender System and more.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- A student posts random texts in a social networking. The social networking can then recommend items to advertise to the student\n",
    "\n",
    "- This time we download Facebook's FastText word embeddings and check the plot in TSNE. \n",
    "\n",
    "- We also try random texts to check the sentiments\n",
    "\n",
    "- Lets do some feats with gensim and textblob library "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I feel like computers these days can sense my thoughts and desires or may be listen to what I say. Because everytime I search for a mobile phone, I get a list of mobile phone suggestions in my social networking. \n",
    "\n",
    "Lets find out how is computer our extended brain actually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n",
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package brown to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package brown is already up-to-date!\n",
      "[nltk_data] Downloading package genesis to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package genesis is already up-to-date!\n",
      "[nltk_data] Downloading package inaugural to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package inaugural is already up-to-date!\n",
      "[nltk_data] Downloading package nps_chat to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package nps_chat is already up-to-date!\n",
      "[nltk_data] Downloading package webtext to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package webtext is already up-to-date!\n",
      "[nltk_data] Downloading package treebank to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package treebank is already up-to-date!\n",
      "[nltk_data] Downloading package punkt to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n",
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n",
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
      "[nltk_data]       date!\n",
      "[nltk_data] Downloading package universal_tagset to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package universal_tagset is already up-to-date!\n",
      "[nltk_data] Downloading package maxent_ne_chunker to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package maxent_ne_chunker is already up-to-date!\n",
      "[nltk_data] Downloading package words to\n",
      "[nltk_data]     C:\\Users\\tranq\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package words is already up-to-date!\n",
      "unable to import 'smart_open.gcs', disabling that module\n"
     ]
    }
   ],
   "source": [
    "#Importing all necessary libraries and modules.\n",
    "import nltk\n",
    "from nltk.tokenize import word_tokenize\n",
    "from collections import Counter\n",
    "nltk.download('wordnet')      \n",
    "from nltk.stem import WordNetLemmatizer \n",
    "from nltk.corpus import stopwords\n",
    "nltk.download('stopwords')    \n",
    "\n",
    "#Anything else you will need to download from nltk, just add it here:\n",
    "nltk.download('brown')\n",
    "nltk.download('genesis')\n",
    "nltk.download('inaugural')\n",
    "nltk.download('nps_chat')\n",
    "nltk.download('webtext')\n",
    "nltk.download('treebank')\n",
    "nltk.download('punkt')\n",
    "nltk.download('stopwords')\n",
    "nltk.download('wordnet')\n",
    "nltk.download('averaged_perceptron_tagger')\n",
    "nltk.download('universal_tagset')\n",
    "nltk.download('maxent_ne_chunker')\n",
    "nltk.download('words')\n",
    "\n",
    "\n",
    "#Anything about Gensim could go here\n",
    "import gensim\n",
    "import string\n",
    "from gensim import corpora\n",
    "from gensim.corpora.dictionary import Dictionary\n",
    "from nltk.tokenize import word_tokenize"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Bag-of-words Approach"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We discussed briefly about BOW in our first warmup exercise. If you want to look in detail, just follow this:\n",
    "\n",
    "https://www.freecodecamp.org/news/an-introduction-to-bag-of-words-and-how-to-code-it-in-python-for-nlp-282e87a9da04/. \n",
    "(I know it gets difficult after step 3. So dont worry, we can use the method we used in our warmup exercise, or we can use Counter class in python)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is our sample text. Lets try to tokenize it. But before that lets lowercase it. Lets also get Bag of words from it. Let's try to do text preprocessing in this sample before proceeding to our exercise. This exercise will be fun, trust me. Lets proceed !\n"
     ]
    }
   ],
   "source": [
    "sample_text = \"This is our sample text. Lets try to tokenize it. But before that lets lowercase it. Lets also get Bag of words from it. Let's try to do text preprocessing in this sample before proceeding to our exercise. This exercise will be fun, trust me. Lets proceed !\"\n",
    "print(sample_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's create tokens from the sample text and lowercase it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['this', 'is', 'our', 'sample', 'text', '.', 'lets', 'try', 'to', 'tokenize', 'it', '.', 'but', 'before', 'that', 'lets', 'lowercase', 'it', '.', 'lets', 'also', 'get', 'bag', 'of', 'words', 'from', 'it', '.', 'let', \"'s\", 'try', 'to', 'do', 'text', 'preprocessing', 'in', 'this', 'sample', 'before', 'proceeding', 'to', 'our', 'exercise', '.', 'this', 'exercise', 'will', 'be', 'fun', ',', 'trust', 'me', '.', 'lets', 'proceed', '!']\n"
     ]
    }
   ],
   "source": [
    "tokens = word_tokenize(sample_text)\n",
    "lowercase_tokens = [t.lower() for t in tokens]\n",
    "print(lowercase_tokens)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can simply use FreqDist that we are using in Warmup Project 1 or go for Counter. If you want to learn more about Counter, follow one or two examples from the links:\n",
    "\n",
    "https://www.geeksforgeeks.org/python-counter-objects-elements/\n",
    "\n",
    "https://www.geeksforgeeks.org/python-case-counter-in-string/?ref=rp\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first line of code below creates a counter object, 'bagofwords_1', that allows us to see each token and the frequency. The second line prints the most common 10 tokens along with the frequency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('.', 6), ('lets', 4), ('this', 3), ('to', 3), ('it', 3), ('our', 2), ('sample', 2), ('text', 2), ('try', 2), ('before', 2), ('exercise', 2), ('is', 1)]\n",
      "[('.', 6), ('lets', 4), ('this', 3), ('to', 3), ('it', 3), ('our', 2)]\n"
     ]
    }
   ],
   "source": [
    "bagofwords_sample = Counter(lowercase_tokens)\n",
    "print(bagofwords_sample.most_common(12)) #Lets print some most common words\n",
    "print(bagofwords_sample.most_common(6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Text Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See from above sample, we got 50% of the top 12 most common words is useless. How to proceed then ? \n",
    "\n",
    "As in our warmup exercises, we will do some processing like....\n",
    "\n",
    "Write it here (Double click this cell. Press Shift+Enter after you are done):\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['sample', 'text', 'lets', 'try', 'tokenize', 'lowercase', 'also', 'get', 'bag', 'words', 'let', 'preprocessing', 'proceeding', 'exercise', 'fun', 'trust', 'proceed']\n"
     ]
    }
   ],
   "source": [
    "lst = [words for words in bagofwords_sample if words.isalpha()] #We can see what isalpha() function did to our text\n",
    "\n",
    "words = stopwords.words(\"english\")\n",
    "words_nostops = [word for word in lst if word not in words]\n",
    "\n",
    "print(words_nostops)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now proceeding with word lemmatization. Recall what is lemmatization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('let', 2), ('sample', 1), ('text', 1), ('try', 1), ('tokenize', 1), ('lowercase', 1)]\n"
     ]
    }
   ],
   "source": [
    "lemmatizer = WordNetLemmatizer()\n",
    "\n",
    "lematized_tokens = [lemmatizer.lemmatize(t) for t in words_nostops]\n",
    "\n",
    "BOW = Counter(lematized_tokens)\n",
    "print(BOW.most_common(6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seems now we are ready to move with our exercise now "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Using Gensim for Latent Dirichlet Allocation (LDA)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets recall what is Gensim and why it is used [Answer at bottom]?  What are word embeddings and how do we use it for topic modeling ? Previously we used Word2Vec, this time we are using Facebook's FastText. \n",
    "\n",
    "To get started, we have created few sample documents. These are represented as post1 to post10 in the lines of code below. These are the posts updated by Mr Jack, in his favorite social networking's profile. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "post1 = \"Today its raining so I can't go out to play\"\n",
    "post2 = \"I like ice hockey, football and basketball and tennis is my favorite\"\n",
    "post3 = \"I want to go to party tonight. Let me know who wants to join me\"\n",
    "post4 = \"Who knows how to play cricket? Let's try some new sports as we have holidays now.\"\n",
    "post5 = \"All work, no plays makes me a dull boy... time to chill\"\n",
    "post6 = \"Who is watching English Premium League tonight  ?\"\n",
    "post7 = \"I want to go to Lapland for my winter holidays.\"\n",
    "post8 = \"Christmas holidays was fun. I enjoyed playing indoor sports with my grandfather.\"\n",
    "post9 = \"Ice cream vs Ice hockey. Now its summer :D\"\n",
    "post10 = \"Summer finished and I didn't play anything all the holidays. #CORONA\"\n",
    "\n",
    "# compile documents\n",
    "corpus = [post1,post2,post3,post4,post5,post6,post7,post8,post9,post10] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Today its raining so I can't go out to play\n"
     ]
    }
   ],
   "source": [
    "print(corpus[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In subsequent sections of this guide, we will try to perform topic modeling on the corpus . As always, the first step is text preprocessing.\n",
    "\n",
    "Notice What we are doing in the first three line of codes. In the fourth to eight lines, we define a function for cleaning the document. Finally, in the last line of code, we use the function to create the cleaned document called 'final_corpus'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "stopwords = set(stopwords.words('english'))  #set removes the reduntant words in the list. If you try running the cell twice it will give error (Know why and what to do)\n",
    "punct = set(string.punctuation)\n",
    "lemma = WordNetLemmatizer()\n",
    "\n",
    "def clean(document):\n",
    "    no_stops = \" \".join([items for items in document.lower().split() if items not in stopwords])\n",
    "    no_punct = ''.join(characters for characters in no_stops if characters not in punct)\n",
    "    lemmatized = \" \".join(lemma.lemmatize(word) for word in no_punct.split())\n",
    "    return lemmatized\n",
    "\n",
    "final_corpus = [clean(document).split() for document in corpus]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before text-cleaning: I like ice hockey, football and basketball and tennis is my favorite\n",
      "After text-cleaning: ['like', 'ice', 'hockey', 'football', 'basketball', 'tennis', 'favorite']\n"
     ]
    }
   ],
   "source": [
    "print(\"Before text-cleaning:\", corpus[1]) \n",
    "\n",
    "print(\"After text-cleaning:\",final_corpus[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remember we used LDA in our WarmupExercise1. Lets recall and follow the same three steps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create dictionary of corpora\n",
    "dictionary = corpora.Dictionary(final_corpus)\n",
    "\n",
    "#Create Document Term Matrix by using doc2bow in our defined corpus (iterate through each documents) in the dictionary above\n",
    "DocTerm_matrix = [dictionary.doc2bow(doc) for doc in final_corpus]\n",
    "\n",
    "#Lets create the LDA object for our topic modeling task\n",
    "Lda_object = gensim.models.ldamodel.LdaModel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now Lets pass our document term matrix to our topic modeling object "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(0, '0.045*\"ice\" + 0.044*\"want\" + 0.043*\"play\"'), (1, '0.054*\"holiday\" + 0.043*\"play\" + 0.029*\"go\"')]\n"
     ]
    }
   ],
   "source": [
    "lda_model_1 = Lda_object(DocTerm_matrix, num_topics=2, id2word = dictionary) # Lets find why we used parameter id2word\n",
    "# https://radimrehurek.com/gensim/models/ldamodel.html\n",
    "\n",
    "print(lda_model_1.print_topics(num_topics=2, num_words=3))  #Lets print out a few topics and decide how many words we use for each"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "In the output above, each line represents a topic with individual topic terms and term-weights. Both topics reveal that Mr Jack is interested in playing some sports. \n",
    "\n",
    "Hmmm....so I can see that Mr Jack is an outgoing, social and sporty person. All these even with this small amount of data we have!\n",
    "\n",
    "Feel free to play around with the parameters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Did you figure out yet what are the scores behind each word ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-4.3995891e-04, -5.9002801e-04, -1.4734648e-03, -1.5346294e-03,\n",
       "       -5.2688498e-04,  1.4499611e-03,  1.3058658e-03, -1.4518567e-03,\n",
       "       -4.5519619e-04,  1.1555931e-03,  8.7376620e-04, -2.2092029e-03,\n",
       "        3.7936834e-04, -6.8273584e-05,  9.2367135e-04,  2.4752908e-05,\n",
       "       -1.0614240e-04,  1.2133257e-03,  1.5453035e-04,  2.0559414e-03,\n",
       "        1.3524544e-04, -2.6840037e-03, -1.2730325e-03, -1.2154239e-03,\n",
       "        1.4191117e-03, -1.2528265e-03,  1.4707792e-03,  8.4391586e-04,\n",
       "       -2.3897146e-03, -3.1444223e-03, -1.7555342e-03, -1.2490597e-03,\n",
       "       -7.4979302e-04, -2.5614086e-03, -2.1778126e-03, -3.0336232e-04,\n",
       "       -2.8601438e-03,  1.6509618e-03,  2.3794184e-03,  1.6232150e-03,\n",
       "       -2.3689542e-03,  2.1412484e-03,  1.8038643e-04,  7.2827586e-04,\n",
       "        4.5768867e-04, -1.1199673e-03,  1.1184127e-03,  7.2761701e-04,\n",
       "        1.0127439e-03,  1.3346094e-04,  1.7920235e-04,  5.0976028e-04,\n",
       "        3.1630162e-04, -3.1719052e-03,  3.3296486e-03, -7.5840706e-04,\n",
       "       -2.6453569e-04,  1.2425533e-03, -2.5037006e-03, -3.0405773e-03,\n",
       "        2.6093039e-03,  2.0944057e-03,  1.3425353e-03,  2.8584350e-04,\n",
       "       -7.8207685e-04, -3.3772894e-04,  1.8789483e-03,  1.6074799e-03,\n",
       "        1.4608377e-03,  1.3102167e-03,  7.5256987e-04,  7.2066300e-04,\n",
       "       -7.7892025e-04,  3.1309630e-04,  4.5638604e-04, -1.1326841e-03,\n",
       "        1.5739173e-03, -7.4770575e-04, -9.9479698e-04, -1.1006627e-03,\n",
       "       -2.2376090e-04,  1.0711618e-03,  2.1718661e-03, -1.4432539e-03,\n",
       "        1.1142653e-03, -1.0847602e-03, -6.7989028e-04, -3.1555181e-03,\n",
       "        2.3571067e-03,  3.1613871e-03,  1.9945172e-03,  5.8694638e-04,\n",
       "        2.0115776e-03,  1.2565878e-03,  1.0198982e-03,  5.4063585e-06,\n",
       "        9.7366411e-04,  1.1133179e-03,  2.4757520e-03,  7.7044839e-05],\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from gensim.models import FastText\n",
    "model = FastText(final_corpus, min_count=1)  #if we have the word at least once in our trained corpus\n",
    "sport_vector = model.wv['sport']\n",
    "sport_vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tranq\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: DeprecationWarning: Call to deprecated `most_similar` (Method will be removed in 4.0.0, use self.wv.most_similar() instead).\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[('want', 0.22497132420539856),\n",
       " ('party', 0.2173389345407486),\n",
       " ('finished', 0.21415047347545624),\n",
       " ('time', 0.17290306091308594),\n",
       " ('tennis', 0.16843661665916443),\n",
       " ('cant', 0.13435709476470947),\n",
       " ('lapland', 0.10359989106655121)]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#model.similar_by_vector(sport_vector, topn=10, restrict_vocab=None)\n",
    "lst = model.most_similar(positive=['sport'], topn = 7)\n",
    "#model.most_similar('sport')[:10]\n",
    "lst"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not so good. But can we now do POS tagging and proceed for advertising?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['want', 'party', 'finished', 'time', 'tennis', 'cant', 'lapland']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "advert=[]\n",
    "for tpl in lst:\n",
    "    advert.append(tpl[0])\n",
    "advert"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('want', 'ADJ'),\n",
       " ('party', 'NOUN'),\n",
       " ('finished', 'VERB'),\n",
       " ('time', 'NOUN'),\n",
       " ('tennis', 'NOUN'),\n",
       " ('cant', 'NOUN'),\n",
       " ('lapland', 'NOUN')]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pos_tag = nltk.pos_tag(advert,tagset = 'universal')  \n",
    "pos_tag"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data we crunched was not good enough to do the magic tricks. What if 5 students with common interest collect 50 different posts and try playing with our bigger corpus ? That can go as an additional task"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  party/NOUN\n",
      "  time/NOUN\n",
      "  tennis/NOUN\n",
      "  cant/NOUN\n",
      "  lapland/NOUN)\n"
     ]
    }
   ],
   "source": [
    "from nltk import ne_chunk #why did we import this ?\n",
    "\n",
    "named_entity = nltk.ne_chunk(pos_tag)\n",
    "\n",
    "#Lets try to print only the names\n",
    "for x in str(named_entity).split('\\n'):\n",
    "    if 'NOUN' in x:\n",
    "        print(x)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "So now I get it. These Natural Language Processing models actually crunch on our data to get valuable information about us"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Great! Now is it possible to append all these in a list so that it can be used for advertising these items in the list to Mr Jack? Think of what you have to offer Mr Jack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "###Your code goes here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even with our small corpus we see there are 3 similar words like tennis, basketball. Lets check with Fasttext, which uses a lots of corpus( 999999 vectors of dimension 300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('sports', 0.8734080791473389),\n",
       " ('non-sport', 0.8134778738021851),\n",
       " ('sporting', 0.7916890382766724),\n",
       " ('sport-', 0.7534786462783813),\n",
       " ('non-sporting', 0.7505502700805664),\n",
       " ('sport-related', 0.7370049953460693),\n",
       " ('sport.', 0.7366814613342285),\n",
       " ('para-sport', 0.7300988435745239),\n",
       " ('sporter', 0.7264223098754883),\n",
       " ('football', 0.7231776714324951)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Press 'ctrl+/' if you want to comment/uncomment. Select all the text first\n",
    "import gensim.downloader as api\n",
    "fasttext_model300 = api.load('fasttext-wiki-news-subwords-300')  #Downloading will take time so be patient\n",
    "fasttext_model300.most_similar(['sport'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Following is the snapshot of the embeddings that we just downloaded. What do you think are these numbers ?"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('sports', 0.8734080791473389),\n",
       " ('non-sport', 0.8134778738021851),\n",
       " ('sporting', 0.7916890382766724),\n",
       " ('sport-', 0.7534786462783813),\n",
       " ('non-sporting', 0.7505502700805664),\n",
       " ('sport-related', 0.7370049953460693),\n",
       " ('sport.', 0.7366814613342285)]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.most_similar(positive=['sport'], topn = 7)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Recall what these code snippets do"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tranq\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:6: DeprecationWarning: Call to deprecated `__getitem__` (Method will be removed in 4.0.0, use self.wv.__getitem__() instead).\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "labels = []   \n",
    "tokens = []  \n",
    "'''The vocabulary is in the vocab field of the Word2Vec model's wv property, as a dictionary, with \n",
    "the keys being each token (word).'''\n",
    "for word in model.wv.vocab:  #model.wv is the mapping between word and vectors (keyed vector) we discussed in above cell also\n",
    "    tokens.append(model[word])   #This is array of the features of the word\n",
    "    labels.append(word)   #And this is list of course"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No need to implement TSNE by your own. But if you feel confindent, try writing code of your own. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from sklearn.manifold import TSNE\n",
    "def tsne_plot(model):\n",
    "    \"Creates a TSNE model and plots it\"\n",
    "    labels = []   \n",
    "    tokens = []   \n",
    "\n",
    "    '''The vocabulary is in the vocab field of the Word2Vec model's wv property, as a dictionary, with \n",
    "    the keys being each token (word).'''\n",
    "    for word in model.wv.vocab:  #model.wv is the mapping between word and vectors (keyed vector) we discussed in above cell also\n",
    "        tokens.append(model[word])   #This is array of the features of the word\n",
    "        labels.append(word)   #And this is list of course\n",
    "    \n",
    "    tsne_model = TSNE(perplexity=40, n_components=2, init='pca', n_iter=2500, random_state = 0) #Try varying n_iter & perplexity\n",
    "    new_values = tsne_model.fit_transform(tokens)  \n",
    "\n",
    "    x = []   #Are these the x and y coordinates ?\n",
    "    y = []\n",
    "    for value in new_values:\n",
    "        x.append(value[0])\n",
    "        y.append(value[1])\n",
    "        \n",
    "    plt.figure(figsize=(12, 12))   #Make figure little bigger/smaller ?\n",
    "    for i in range(len(x)):\n",
    "        plt.scatter(x[i],y[i])    \n",
    "        plt.annotate(labels[i],     \n",
    "                     xy=(x[i], y[i]),\n",
    "                     xytext=(5, 5),\n",
    "                     textcoords='offset pixels',\n",
    "                     ha='left',\n",
    "                     va='top')\n",
    "    \n",
    "\n",
    "\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tranq\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:12: DeprecationWarning: Call to deprecated `__getitem__` (Method will be removed in 4.0.0, use self.wv.__getitem__() instead).\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsne_plot(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have a large corpus from exercise#1 in this notebook, lets try plotting them (This time try coding yourself)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Your Code goes here "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Q: Is it possible to plot the fasttext_model300 ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's Play the Odd one out game "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\tranq\\Anaconda3\\lib\\site-packages\\gensim\\models\\keyedvectors.py:877: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
      "  vectors = vstack(self.word_vec(word, use_norm=True) for word in used_words).astype(REAL)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'bone'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.doesnt_match(\"cat dog bone rabbit\".split())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cool! Create some of your own now "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now Lets try one powerful feature possible from word embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('cats', 0.7978489995002747),\n",
       " ('dogs', 0.7878663539886475),\n",
       " ('puppy', 0.7869204878807068),\n",
       " ('dogs-', 0.7802255153656006),\n",
       " ('pet', 0.775253415107727),\n",
       " ('beagle', 0.7698754072189331),\n",
       " ('labrador', 0.7631130218505859),\n",
       " ('kitten', 0.7627809047698975),\n",
       " ('housecat', 0.7518125772476196),\n",
       " ('staffy', 0.7477413415908813)]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.most_similar(['cat','dog'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('queen', 0.778674840927124),\n",
       " ('queen-mother', 0.7143871188163757),\n",
       " ('king-', 0.6981282234191895),\n",
       " ('queen-consort', 0.6724598407745361),\n",
       " ('monarch', 0.666700005531311)]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.most_similar(positive=['woman','king'], negative=['man'], topn = 5) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Q: What is the parameter negative doing ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dont wait! Try something more!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Katmandu', 0.7372826933860779),\n",
       " ('Stockholm', 0.6841224431991577),\n",
       " ('Bangkok', 0.6750401258468628),\n",
       " ('Pokhara', 0.673894464969635),\n",
       " ('Stockholm-Arlanda', 0.6669442057609558),\n",
       " ('Finland', 0.6629941463470459),\n",
       " ('Kamppi', 0.6556113362312317),\n",
       " ('Tampere', 0.6543558835983276),\n",
       " ('Delhi', 0.6527150869369507),\n",
       " ('Toijala', 0.6506778001785278)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.most_similar(['Kathmandu','Helsinki'], topn=10)  #Lets try now what is the similarities between two capitals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you think could be the score beside each City?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Japan', 0.8723644614219666)]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.most_similar(positive=['Tokyo','Finland'], negative=['Helsinki'], topn = 1)\n",
    "#What are we doing ? Subtracting Tokyo and Finland from Helsinki ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you think the above code is doing ? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you think is the default value of topn ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Turku', 0.6103343963623047),\n",
       " ('Oulu', 0.5967726707458496),\n",
       " ('Finnish', 0.5943154692649841),\n",
       " ('Finnish-speaking', 0.5740379095077515),\n",
       " ('Finnland', 0.5694271326065063),\n",
       " ('Jyväskylä', 0.5682488679885864),\n",
       " ('Finlands', 0.5638313889503479),\n",
       " ('Kuopio', 0.5532369613647461),\n",
       " ('Sweden', 0.5465379953384399),\n",
       " ('Tampere', 0.5453804135322571)]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fasttext_model300.most_similar(positive=['Helsinki','Finland', 'Germany'], negative=['Berlin', 'Sweeden'])\n",
    "#What the heck did I do and what did i get ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('My', 'PRP$'),\n",
       " ('Text', 'NN'),\n",
       " ('goes', 'VBZ'),\n",
       " ('here', 'RB'),\n",
       " ('Mr', 'NNP'),\n",
       " ('Jack', 'NNP'),\n",
       " ('is', 'VBZ'),\n",
       " ('a', 'DT'),\n",
       " ('good', 'JJ'),\n",
       " ('player', 'NN'),\n",
       " ('and', 'CC'),\n",
       " ('he', 'PRP'),\n",
       " ('is', 'VBZ'),\n",
       " ('a', 'DT'),\n",
       " ('social', 'JJ'),\n",
       " ('boy', 'NN'),\n",
       " ('I', 'PRP'),\n",
       " ('think', 'VBP'),\n",
       " ('in', 'IN'),\n",
       " ('future', 'NN'),\n",
       " ('he', 'PRP'),\n",
       " ('will', 'MD'),\n",
       " ('be', 'VB'),\n",
       " ('a', 'DT'),\n",
       " ('good', 'JJ'),\n",
       " ('national', 'JJ'),\n",
       " ('ice', 'NN'),\n",
       " ('hockey', 'NN'),\n",
       " ('player', 'NN'),\n",
       " ('I', 'PRP'),\n",
       " ('just', 'RB'),\n",
       " ('wish', 'VB'),\n",
       " ('he', 'PRP'),\n",
       " ('doesnt', 'VB'),\n",
       " ('earn', 'RB'),\n",
       " ('bad', 'JJ'),\n",
       " ('name', 'NN'),\n",
       " ('due', 'JJ'),\n",
       " ('to', 'TO'),\n",
       " ('losing', 'VBG'),\n",
       " ('some', 'DT'),\n",
       " ('games', 'NNS')]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from textblob import TextBlob\n",
    "\n",
    "text = \"My Text goes here. Mr Jack is a good player and he is a social boy. I think in future he will be a good national ice hockey player. I just wish he doesnt earn bad name due to losing some games.\"\n",
    "\n",
    "blob = TextBlob(text)\n",
    "blob.tags  #This will give all of the tags, i.e. Parts of Speech          \n",
    "#blob.words.count('My')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check out the meaning of the tags:\n",
    "\n",
    "- CC coordinating conjunction\n",
    "- CD cardinal digit\n",
    "- DT determiner\n",
    "- EX existential there (like: “there is” … think of it like “there exists”)\n",
    "- FW foreign word\n",
    "- IN preposition/subordinating conjunction\n",
    "- JJ adjective ‘big’\n",
    "- JJR adjective, comparative ‘bigger’\n",
    "- JJS adjective, superlative ‘biggest’\n",
    "- LS list marker 1)\n",
    "- MD modal could, will\n",
    "- NN noun, singular ‘desk’\n",
    "- NNS noun plural ‘desks’\n",
    "- NNP proper noun, singular ‘Harrison’\n",
    "- NNPS proper noun, plural ‘Americans’\n",
    "- PDT predeterminer ‘all the kids’\n",
    "- POS possessive ending parent‘s\n",
    "- PRP personal pronoun I, he, she\n",
    "\n",
    "- PRP$ possessive pronoun my, his, hers\n",
    "\n",
    "- RB adverb very, silently,\n",
    "- RBR adverb, comparative better\n",
    "- RBS adverb, superlative best\n",
    "- RP particle give up\n",
    "- TO to go ‘to‘ the store.\n",
    "- UH interjection errrrrrrrm\n",
    "- VB verb, base form take\n",
    "- VBD verb, past tense took\n",
    "- VBG verb, gerund/present participle taking\n",
    "- VBN verb, past participle taken\n",
    "- VBP verb, sing. present, non-3d take\n",
    "- VBZ verb, 3rd person sing. present takes\n",
    "- WDT wh-determiner which\n",
    "- WP wh-pronoun who, what\n",
    "\n",
    "- WP$ possessive wh-pronoun whose\n",
    "\n",
    "- WRB wh-abverb where, when"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WordList(['text', 'mr jack', 'good player', 'social boy', 'good national ice hockey player', 'bad name'])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blob.noun_phrases   #This will give you the noun phrases only"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You will come across many websites which classify text realtime, or which can do realtime sentiment analysis. We cant do this as it is out of the scope of our course. But lets try something here. Try typing your text here and determine if it is a positive or a negative sentiment type. (Recall what is polarity and what is subjectivity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n",
      "0.36666666666666664\n",
      "0.35\n",
      "-0.4124999999999999\n"
     ]
    }
   ],
   "source": [
    "# blob.sentences # We have three sentences which we can access easily using the blob object\n",
    "for sentence in blob.sentences:\n",
    "    print(sentence.sentiment.polarity)  #This prints the polarity of all the three sentences"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Lets consider a score of -0.1 - 0.99 to be neutral, \n",
    "\n",
    "below -0.1 to be negative and \n",
    "\n",
    "a score of 0.1 and above to be positive"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So what can you intrepret ? Is it possible to say if the sentence is neutral, positive or negative ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "My Text goes here. : 0.0\n",
      "Mr Jack is a good player and he is a social boy. : 0.36666666666666664\n",
      "I think in future he will be a good national ice hockey player. : 0.35\n",
      "I just wish he doesnt earn bad name due to losing some games. : -0.4124999999999999\n",
      "\n",
      "0.0 neutral\n",
      "0.36666666666666664 positive\n",
      "0.35 positive\n",
      "-0.4124999999999999 negative\n"
     ]
    }
   ],
   "source": [
    "polarity = []\n",
    "for index,sentence in enumerate(blob.sentences):\n",
    "    print(sentence,':',sentence.sentiment.polarity)\n",
    "    polarity.append(sentence.sentiment.polarity)\n",
    "    \n",
    "print()\n",
    "\n",
    "for idx,sentiment in enumerate(polarity):\n",
    "    if sentiment < 0.1 and sentiment >-0.1:\n",
    "        print(polarity[idx],\"neutral\")\n",
    "    elif sentiment > 0.1:\n",
    "        print(polarity[idx],\"positive\")\n",
    "    else:\n",
    "        print(polarity[idx],\"negative\")"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Lets make it a bit convenient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "My Text goes here. : has score of 0.0  - Is a neutral statement\n",
      "Mr Jack is a good player and he is a social boy. : has score of 0.36666666666666664  - Is a positive statement\n",
      "I think in future he will be a good national ice hockey player. : has score of 0.35  - Is a positive statement\n",
      "I just wish he doesnt earn bad name due to losing some games. : has score of -0.4124999999999999  - Is a negative statement\n"
     ]
    }
   ],
   "source": [
    "polarity = []\n",
    "for sentence in blob.sentences:\n",
    "    if sentence.sentiment.polarity < 0.1 and sentence.sentiment.polarity >-0.1:\n",
    "        print(sentence,': has score of',sentence.sentiment.polarity,' - Is a neutral statement')\n",
    "    elif sentence.sentiment.polarity > 0.1:\n",
    "        print(sentence,': has score of',sentence.sentiment.polarity,' - Is a positive statement')\n",
    "    else:\n",
    "        print(sentence,': has score of',sentence.sentiment.polarity,' - Is a negative statement')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a  lot of fancy things we can try with textblog. \n",
    "Check out this guide and try at least 5 stuffs that intrigues you. \n",
    "\n",
    "https://textblob.readthedocs.io/en/dev/quickstart.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Cool! By now we have known that what magics and feats we can play on text data and how computers can utilize our typed data. But do you think computers can really listen to us ? "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets follow this article:\n",
    "\n",
    "https://towardsdatascience.com/building-a-speech-recognizer-in-python-2dad733949b4\n",
    "\n",
    "You can try implementing that if you want. \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Code goes here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "What is Gensim, its usage and what are word embeddings ?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Gensim is an open-source library for unsupervised topic modeling and natural language processing, using modern statistical machine learning. Gensim is implemented in Python and Cython. [Wikipedia]\n",
    "\n",
    "Used for: Creating and querying corpus\n",
    "\n",
    "Word vectors are multi-dimensional mathematical representations of words created using deep learning methods. They give us insight into relationships between terms in a corpus. For example, the distance between the two words 'India' and 'New Delhi' might be similar to the distance between 'China' and 'Beijing', as these represent the 'Country-Capital' vectors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Further Fun Exercise: \n",
    "\n",
    "If you use chrome, try the link below:\n",
    "\n",
    "https://myactivity.google.com/myactivity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What did you notice ? \n",
    "\n",
    "Personally I use some extensions to avoid excessive of data tracking by the browser. In all browsers, you have options of adding extensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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