classifiying the sign language using Deep Learning

In this project, I built a Sign Language Digit Classification system using deep learning techniques. The model is trained to recognize hand gesture images representing digits from 0 to 9. The project is implemented using TensorFlow and Keras in Google Colab, and it leverages MobileNetV2 (transfer learning) to achieve high accuracy and efficient performance. Key Features: * Image classification of hand signs (0–9) * Dataset preprocessing and splitting (train, validation, test) * Deep learning model using MobileNetV2 * Model training and evaluation * Confusion matrix visualization * Real-time prediction on new images Technologies Used: * Python * TensorFlow / Keras * Google Colab * MobileNetV2 * OpenCV