Many newcomers to deep learning often rely heavily on stochastic gradient descent without fully understanding its mechanics. This approach can lead to issues, particularly when the algorithm gets trapped in local minima, resulting in suboptimal solutions for certain problems. It's crucial to consider these limitations when applying deep learning techniques.
