I have utilized Deep Learning, a type of Machine Learning, to efficiently profile celebrities on Twitter. This involved categorizing tweets into six domains: Business, Sports, Entertainment, Education, Technology, and Politics. To do this, I employed text mining techniques to extract features such as sentiment scores, mentions, hashtags, and word frequencies from the tweets. Next, I utilized NLP algorithms to analyze this extracted data. For each document, I created a data dictionary that displays the number of occurrences for each word, indicating how frequently each word appears. Using this methodology, I gathered and processed tweets from an unknown celebrity, removed irrelevant information, and compared the resulting data dictionary to identify the category or genre that the celebrity belongs to.