sdoshi579

import nltk
nltk.download()

import nltk
from nltk.tokenize import RegexpTokenizer

text = 'Citizens of India are known as Indians.'

# By passing r'\w+' to the RegexpTokenizer

sdoshi579

import fastText
import sys
import os
import nltk
nltk.download('punkt')
import csv
import datetime
from bs4 import BeautifulSoup
import re
import itertools

sdoshi579

%pylab inline
import os
import numpy as np
import pandas as pd
from scipy.misc import imread
from sklearn.metrics import accuracy_score

import tensorflow as tf
import keras
from keras.layers import Dense, Dropout, Flatten

sdoshi579

import librosa
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import os
import csv
# Preprocessing
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder, StandardScaler

sdoshi579

import os
import pandas as pd
from scipy.misc import imread
import math
import numpy as np
import cv2
import keras
import seaborn as sns
from keras.layers import Dense, Dropout, Flatten, Input
from keras.layers import Conv2D, MaxPooling2D

sdoshi579

import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
import nltk
from sklearn.decomposition import TruncatedSVD
# If nltk stop word is not downloaded
# nltk.download('stopwords')
from nltk.corpus import stopwords

# List of documents
a1 = "He is a good dog."