Social media platforms serve as crucial sources of information for understanding public opinion and sentiments on various topics and issues. Many individuals spend countless hours every day sharing their thoughts, reactions, and viewpoints with others. To evaluate the sentiment of people's opinions toward a particular topic, tweets extracted from Twitter related to a particular topic using the Twitter API. Machine learning techniques were then employed to analyze the collected tweets as either positive, negative, or neutral. This study employs Python programming to conduct experiments on different tweets obtained through the Twitter API. NLTK library was used for tweet preprocessing, and TextBlob was utilized to analyze the tweet dataset. The study then presents interesting results through different visualizations of positive, negative, and neutral sentiments.