Sign_Language_Classification

• Built a deep learning model to classify 36 hand gestures from the American Sign Language (ASL) dataset.
• Used TensorFlow, Keras, and data augmentation techniques (ImageDataGenerator and splitfolders etc), implementing a CNN with layers including Conv2D, MaxPooling, Dropout, and softmax.
• Used ReduceLROnPlateau for adaptive learning rates and EarlyStopping to prevent overfitting. -Achieved an impressive 97% accuracy on an independent test set, demonstrating strong generalization and reliability.