Example Concept: To improve a neural network's accuracy in image classification, start by augmenting your dataset with techniques like rotation, scaling, and flipping to increase diversity. Use transfer learning by leveraging pre-trained models and fine-tuning them on your specific dataset. Additionally, experiment with different architectures and hyperparameters, such as learning rate and batch size, and employ regularization techniques like dropout to prevent overfitting.