input: Write a python function to classify sentiment of tweets based on predefined positive and negative words.
  assert classify_sentiment("I love this product, it is amazing!") == "positive"
  assert classify_sentiment("This is a terrible experience, I hate it!") == "negative"
  assert classify_sentiment("The movie was okay, not good, not bad.") == "neutral"
output: def classify_sentiment(tweet):
      positive_words = {'love', 'amazing', 'good', 'great', 'fantastic', 'excellent'}
      negative_words = {'terrible', 'hate', 'bad', 'awful', 'horrible', 'poor'}
      
      tweet_words = set(tweet.lower().split())
      
      positive_count = len(tweet_words & positive_words)
      negative_count = len(tweet_words & negative_words)
      
      if positive_count > negative_count:
          return "positive"
      elif negative_count > positive_count:
          return "negative"
      else:
          return "neutral"