Preprocessing steps may include tokenization, stemming, and removing stop words. Libraries like NLTK and spaCy provide functions for these tasks.
Example Code:
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
text = "This is an example sentence."
tokens = word_tokenize(text)
stop_words = set(stopwords.words('english'))
filtered_tokens = [word for word in tokens if word.lower() not in stop_words]
ps = PorterStemmer()
stemmed_tokens = [ps.stem(word) for word in filtered_tokens]
print(stemmed_tokens)
