NLP, Python, Data Science, Computer Science, Natural Language Processi.
tokens = re.split('\s+', text) tokens = [t.lower() for t in tokens] tokens = [t for t in tokens if t not in stopwords] tokens = [stemmer.stem(word) for word in tokens if word in vocab_1 or word in vocab_2 or word in valid_words or word in modal_verbs or stemmer.stem(word) in vocab_1 or