Nowadays, social media platforms like Twitter are widely used by people to express their opinions on different topics such as products, politics, and social issues. Every day, a large amount of data is generated in the form of tweets, which are usually short and unstructured.

Analyzing this data manually is very difficult and time-consuming. So, in this project, we use sentiment analysis to automatically identify whether a tweet is positive, negative, or neutral.

First, the data is cleaned by removing unwanted elements like special characters, URLs, and stop words. Then, the text is converted into numerical form using TF-IDF technique.

After that, machine learning algorithms are applied to classify the tweets into different sentiment categories. This system helps in understanding public opinion easily and can be useful for businesses and researchers.