input: Write a python function to predict the sentiment of a tweet using nltk's SentimentIntensityAnalyzer.
  assert predict_sentiment("I love sunny days!") == 'Positive'
  assert predict_sentiment("I am feeling really down today.") == 'Negative'
  assert predict_sentiment("It's an okay day.") == 'Neutral'
output: def predict_sentiment(tweet):
      from nltk.sentiment import SentimentIntensityAnalyzer
      sia = SentimentIntensityAnalyzer()
      sentiment = sia.polarity_scores(tweet)
      if sentiment['compound'] >= 0.05:
          return 'Positive'
      elif sentiment['compound'] <= -0.05:
          return 'Negative'
      else:
          return 'Neutral'