input: Write a function to read in a tweet and remove all punctuation, special characters, and stopwords from the tweet.
  assert clean_tweet("I'm so excited to be going to the #MuseumTour! #BigDay #travel") == ['excited', 'going', 'MuseumTour', 'BigDay', 'travel']
  assert clean_tweet("On my way to the meeting with @client123.") == ['way', 'meeting', 'client123']
  assert clean_tweet("#NewProduct Launch is going great! #business") == ['NewProduct', 'Launch', 'going', 'great', 'business']
  assert clean_tweet("Excited for the @TechConference next week!") == ['Excited', 'TechConference', 'week']
  assert clean_tweet("") == []
output: def clean_tweet(tweet):
      import re
      from nltk.corpus import stopwords
      stop_words = set(stopwords.words('english'))
      words = re.findall(r'\b\w+\b', tweet)
      cleaned_words = [word for word in words if word.lower() not in stop_words]
      return cleaned_words