input: def sentiment_analysis(tweets):
      """ Analyze the sentiment of given tweets and classify them as either 'Positive' or 'Negative'.
      >>> sentiment_analysis(['I love this!', 'This is terrible'])
      ['Positive', 'Negative']
      >>> sentiment_analysis(['My day was great', 'I feel awful today'])
      ['Positive', 'Negative']
      """
      # Initialize a list to store the result 
      results = [] 
  
      # Iterate through each tweet
      for tweet in tweets:
          # Clean the tweet 
          tweet = preprocessing(tweet)
  
          # Vectorize the tweet and obtain the prediction 
          tweet_vector = vectorize(tweet)
          prediction = predict_sentiment(tweet_vector)
  
          # Append the prediction to the result list
          if prediction == 1:
              results.append("Positive")
          elif prediction == 0:
              results.append("Negative")
  
      return results
output:     # Initialize a list to store the result 
      results = [] 
  
      # Iterate through each tweet
      for tweet in tweets:
          # Clean the tweet 
          tweet = preprocessing(tweet)
  
          # Vectorize the tweet and obtain the prediction 
          tweet_vector = vectorize(tweet)
          prediction = predict_sentiment(tweet_vector)
  
          # Append the prediction to the result list
          if prediction == 1:
              results.append("Positive")
          elif prediction == 0:
              results.append("Negative")
  
      return results