Example Concept: To enhance a neural network's accuracy in image classification, consider using data augmentation to increase dataset variability, employing transfer learning with pre-trained models for better feature extraction, and tuning hyperparameters such as learning rate and batch size. Additionally, implementing regularization techniques like dropout can prevent overfitting, while using advanced architectures like CNNs (Convolutional Neural Networks) can improve feature learning.