Apple Twitter Sentiment Analysis
In this project, I developed a sentiment analysis tool capable of interpreting the emotional tone behind text inputs. Leveraging a LinearSVC model from Scikit-learn and a TF-IDF Vectorizer for text feature extraction, the tool preprocesses input text by normalizing, removing stop words, and applying lemmatization using the NLTK's WordNetLemmatizer. Designed to evaluate sentiment in user feedback, the model efficiently distinguishes between positive and negative expressions.