Hands-On Python Deep Learning for the Web

Making the necessary imports

We begin by importing the required Python modules to the project:

import numpy as npimport pandas as pdimport nltkfrom nltk.corpus import stopwords from nltk.tokenize import WordPunctTokenizerfrom sklearn.model_selection import train_test_splitfrom sklearn.feature_extraction.text import TfidfVectorizer# Comment below line if you already have stopwords installednltk.download('stopwords')

We import TfidfVectorizer to help us create Term Frequency-Inverse Document Frequency (TF-IDF) vectors for performing natural language processing. TF-IDF is a numerical measure of how important a word in a single document is, given a number of documents that may or may not contain the words. Numerically, it increases the importance ...