input: def sentiment_analysis(tweets):
      """ Classify each tweet as either 'Positive' or 'Negative' based on the sentiment.
      >>> sentiment_analysis(['I love this!', 'I hate this.'])
      ['Positive', 'Negative']
      >>> sentiment_analysis(['What a great day!', 'Bad news.', 'Could be better.'])
      ['Positive', 'Negative', 'Negative']
      """
output:     sentiment_dict = {
          'love': 'Positive',
          'great': 'Positive',
          'good': 'Positive',
          'awesome': 'Positive',
          'hate': 'Negative',
          'bad': 'Negative',
          'terrible': 'Negative',
          'awful': 'Negative'
      }
      
      result = []
      for tweet in tweets:
          sentiment = 'Positive'
          for word in tweet.split():
              word = word.lower().strip('.,!?')
              if word in sentiment_dict:
                  sentiment = sentiment_dict[word]
                  break
          result.append(sentiment)
      
      return result