Deep learning models with fewer than a dozen layers can often achieve impressive accuracy, yet some networks boast hundreds or even thousands of layers. While these complex architectures may offer marginal improvements in specific academic contexts, the real strength of deep learning lies in its versatility across various machine learning tasks. This widespread application is why deep learning and artificial intelligence are frequently conflated in discussions today.
