• Ch Karthik
• P.S.S Pranav
• Ch. Teja
• B. Praveen
• K. Subhadra

In today's age where internet usage is increasing rapidly, we rely on various online news sources. Due to the huge volume and speed of data transmission over the Internet, it is impossible to have every article analyzed by an expert. Even an expert in a certain field has to examine several aspects before passing a verdict on the veracity of an article, such as creating opinions in favor or against certain candidates, or spammers using interesting headlines to make money with click-bait ads. Our goal is to perform binary classification of various news articles and provide the user with the ability to classify news as fake or real using the concepts of natural language processing and machine learning.

"Fake News Detection Using Logistic Regression, Naive Baye's and Random Forest", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 7, page no.a487-a493, July-2023, Available :http://www.jetir.org/papers/JETIR2307060.pdf

"Fake News Detection Using Logistic Regression, Naive Baye's and Random Forest", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 7, page no. ppa487-a493, July-2023, Available at : http://www.jetir.org/papers/JETIR2307060.pdf