Twitter generates massive amount of data that often goes unused and unexplored. This data can be used to get valuable information about the user such as age, gender, nationality, likes and dislikes. This information is very useful in case of targeted marketing, advertisements, legal investigation, riot prediction, trend anticipation, political affiliation etc. The data obtained from twitter however has its own shortcomings because of its restricted character limit of 280 characters. Determination of the gender of the user is quite important. In the fields of fashion, healthcare, employment; Products and services are different for both men and women. This project aims at determining the gender of the user using ML algorithms and aims at comparing these algorithms
