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codebasics
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nltk vs spacy
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‎2_nltk_vs_spacy/Spacy vs NLTK.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<h3>Installation instructions</h3>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"pip install spacy\n",
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"\n",
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"python -m spacy download en"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"pip install nltk"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<h3>Sentence & Word Tokenization In Spacy</h3>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"import spacy"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"nlp = spacy.load(\"en_core_web_sm\")\n",
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"\n",
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"doc = nlp(\"Dr. Strange loves pav bhaji of mumbai. Hulk loves chat of delhi\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Dr. Strange loves pav bhaji of mumbai.\n",
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"Hulk loves chat of delhi\n"
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]
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}
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],
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"source": [
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"for sentence in doc.sents:\n",
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" print(sentence)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Dr.\n",
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"Strange\n",
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"loves\n",
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"pav\n",
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"bhaji\n",
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"of\n",
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"mumbai\n",
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".\n",
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"Hulk\n",
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"loves\n",
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"chat\n",
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"of\n",
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"delhi\n"
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]
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}
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],
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"source": [
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"for sentence in doc.sents:\n",
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" for word in sentence:\n",
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" print(word)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<h3>Sentence & Word Tokenization In NLTK</h3>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[nltk_data] Downloading package punkt to\n",
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"[nltk_data] C:\\Users\\dhava\\AppData\\Roaming\\nltk_data...\n",
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"[nltk_data] Unzipping tokenizers\\punkt.zip.\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from nltk.tokenize import sent_tokenize\n",
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"import nltk\n",
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"nltk.download('punkt')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['Dr.', 'Strange loves pav bhaji of mumbai.', 'Hulk loves chat of delhi']"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"sent_tokenize(\"Dr. Strange loves pav bhaji of mumbai. Hulk loves chat of delhi\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"from nltk.tokenize import word_tokenize"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['Dr',\n",
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" '.',\n",
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" 'Strange',\n",
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" 'loves',\n",
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" 'pav',\n",
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" 'bhaji',\n",
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" 'of',\n",
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" 'mumbai',\n",
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" '.',\n",
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" 'Hulk',\n",
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" 'loves',\n",
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" 'chat',\n",
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" 'of',\n",
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" 'delhi']"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"word_tokenize(\"Dr. Strange loves pav bhaji of mumbai. Hulk loves chat of delhi\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**From above code you can see that Spacy is object oriented whereas NLTK is a string processing library**"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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