Flight Booking Analysis

Associated with "CS CODENZ" and "Chalapathi Institute of Engineering and Technology"

As a part of DS/ML 5 day workshop . The CODENZ Company assigned the project. The aim of this project is maintain the timings and booking seats cost ased on the classes for the passengers to travel their destination without late.

The key features :

1. The data must be efficient and accurate based on the passenger wants from it.

2. The Machine Learning must be updated and estimated with recuression, clustering and regression analysis.

3. The project is uploaded in repo of github.    

Vigilant Guardians: A Unified Approach to Real-time Drowsiness Detection in Drivers using Python, AI, ML, and Facial Recognition 

Associated with "Chalapathi Institute of Engineering and Technology"

1.  Spearheaded the development of an innovative drowsiness detection system utilizing convolutional neural networks (CNNs) and transfer learning techniques, achieving over 96% accuracy in classifying driver drowsiness based on facial features. 

2. Integrated AI, ML, and Python programming to create a real-time facial recognition system for monitoring driver fatigue, aiming to mitigate road accidents caused by drowsiness during long night drives. 

3. Led a comprehensive project addressing the critical road safety concern of driver drowsiness, employing advanced classification algorithms such as K-Nearest Neighbors, and CNNs to develop a robust solution for proactive drowsiness detection and prevention.