Description: Social media sites are used on a regular basis in today's world and have become an integral part of our lives. It is one of the main means of communication and has become a tool for both spammers and scammers. Such social media platforms have changed drastically how we live our social life. It has become easier to make new friends, keep in touch with them, and know their updates. But many problems, such as fake profiles and online impersonation, have also grown with the rapid growth of social media. This project presents a machine learning(Neural Network) method for detecting fake accounts in social media. In this work a study is carried out of different research papers and provides a comparative study of existing work done. Fake accounts are mostly used by intruders to perform malicious activities such as personal identity harm, theft, and privacy intrusion on social media platforms. Hence identifying an account is either real or fake is one of the key issues.

Technology used:

Anaconda, Sublime Text Editor

1.Programming Language – Python

2. Algorithm used – Neural Network

3.Libraries – NumPy, Pandas, TensorFlow, Streamlit

Github link :

https://github.com/dipikamahajan7799/Detection-Of-Fake-Profile-In-Online-Social-Networking-Using-Machine-Learning..git

Description: Black spot is a place where road traffic accident have historically been concentrated According to past data,accident occur when the driver is Sleepy or negligent,Moving with high speed, Because of bad condition of roads sending an alert when the driver is within the range of black spots, so that they will become active and slow down their vehical, avoiding accident.

Technology used:

Html, Css, Javascript, Php, MySQL, etc

Tools:

Xampp, Sublime Text Editor, etc

Github link :

https://github.com/dipikamahajan7799/Black-Spot-Alert-On-Mobile-Phone-For-Travellers.git