input: Write a function to analyze the sentiment of a sentence using nltk's SentimentIntensityAnalyzer.
  assert sentiment_analyzer('I love this movie!') == 'positive'
  assert sentiment_analyzer('I hate this place!') == 'negative'
  assert sentiment_analyzer('It is an okay day.') == 'neutral'
  assert sentiment_analyzer('This is absolutely wonderful!') == 'positive'
  assert sentiment_analyzer('I am not happy with the service.') == 'negative'
output: def sentiment_analyzer(sentence):
      from nltk.sentiment import SentimentIntensityAnalyzer
      sia = SentimentIntensityAnalyzer()
      scores = sia.polarity_scores(sentence)
      if scores['compound'] >= 0.05:
          return 'positive'
      elif scores['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'