input: Write a function to analyze sentiment of a sentence using NLTK's VADER SentimentIntensityAnalyzer.
  assert analyze_sentiment("I love spending time with my family") == "Positive Sentiment"
  assert analyze_sentiment("I hate getting up early in the morning") == "Negative Sentiment"
  assert analyze_sentiment("It's an average day with nothing special happening") == "Neutral Sentiment"
output: def analyze_sentiment(sentence):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon')
      
      sia = SentimentIntensityAnalyzer()
      score = sia.polarity_scores(sentence)
      
      if score['compound'] >= 0.05:
          return "Positive Sentiment"
      elif score['compound'] <= -0.05:
          return "Negative Sentiment"
      else:
          return "Neutral Sentiment"