📦 Import Libraries
import numpy as np
import pandas as pd
import sklearn as skl
import matplotlib.pyplot as plt
-
numpy
,pandas
: Data manipulation -
sklearn
: ML tools like vectorizers and train/test split -
matplotlib
: Visualization (optional)
📚 NLP Preprocessing Setup
import re
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
-
re
: Regex for text cleaning -
nltk
: Tokenization, stopwords, and stemming
🚫 Custom Stopwords
negatives = ['no', 'nor', 'not', "don't", ...]
all_stopwords = [w for w in stopwords.words('english') if w not in negatives]
Retains negative words like “not”, which are important for sentiment.