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The Deep Learning Optimizer skill enables Claude to intelligently enhance the performance and efficiency of neural networks. By analyzing existing model architectures, training data, and performance metrics, the skill automatically identifies bottlenecks and applies advanced optimization techniques such as Adam or SGD selection, learning rate scheduling, and regularization strategies. It is particularly useful for developers looking to maximize model accuracy, minimize resource consumption, or significantly reduce training time without the need for manual trial-and-error hyperparameter tuning.