This project involves developing a Traffic Sign Detection and Recognition system using a deep learning model built with Keras. Its goal is interpreting traffic signs in real-time.
-
Updated
Nov 20, 2024 - Python
This project involves developing a Traffic Sign Detection and Recognition system using a deep learning model built with Keras. Its goal is interpreting traffic signs in real-time.
Deep Learning
Code for classifying hand-sign image dataset using a supervised learning approach: Neural Network with some technique to improve the accuracy metric.
End-to-end time series forecasting using both Machine Learning and Deep Learning models. Includes data preprocessing, EDA, feature scaling, and performance evaluation on real-world datasets.
To associate your repository with the sequential-model topic, visit your repo's landing page and select "manage topics."