Data Science Project 7

Traffic sign classification is an important task for self-driving cars. In this project, a Deep Network known as LE-NET will be used for traffic sign image classification. The objective is to design a machine-learning model that can accurately detect and classify traffic signs from images and real-time video streams.
We aim to create a robust system capable of recognizing and interpreting a wide range of signs, from speed limits to yield or stop signs, contributing to a safer and more efficient transportation system.

• Gather a diverse dataset of traffic sign images, encompassing various shapes, colors, and conditions.
• Choose an appropriate machine learning or deep learning architecture for image classification
• Evaluate the Model’s performance on real-world traffic sign recognition tasks.
• Address ethical concerns related to the deployment of AI in safety-critical systems, ensuring fairness and transparency