Sentiment Analysis is process or technique that determine the emotional tone of a text whether it is positive, negative, or neutral using machine learning. Nowadays, social media generates a huge amount of text data from blogs, comments, and other sources. It takes a lot of time and money for an individual to analyse the sentiment in this data, thus a classification model is utilized instead. Navie Bayes is one of the finest classification models. Navie Bayes is designed based on Bayes theorem that mostly used for text categorization, to implement this model twitter dataset from Kaggle is used. A web-based approach is implemented to check the emotion of the person based on text. The joblib library is used to save the trained model, which is then imported into the Django project where an input form is provided, and the sentiment type positive or negetive or neutral is displayed as a result. The model's performence is evaluated using accuracy metric.