input: Write a python function to perform sentiment analysis on a given text using NLTK's VADER sentiment analyzer.
  assert sentimentAnalysis("I love this product, it's amazing!") == 'positive'
  assert sentimentAnalysis("This is the worst experience I've ever had.") == 'negative'
  assert sentimentAnalysis("It's okay, not great but not terrible either.") == 'neutral'
output: def sentimentAnalysis(text):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon')
      
      sid = SentimentIntensityAnalyzer()
      sentiment_scores = sid.polarity_scores(text)
      
      if sentiment_scores['compound'] >= 0.05:
          return 'positive'
      elif sentiment_scores['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'