Adam's Mountain

Adam's Mountain refers to a concept in optimization, often used in machine learning, resembling a landscape with peaks and valleys representing different solutions. When training models, algorithms like Adam navigate this terrain to find the lowest point, which corresponds to the best model parameters. Adam's method adapts the step size and direction during this journey, making it efficient at avoiding pitfalls like getting stuck in suboptimal solutions. Think of it as a smart hiker using terrain information to reach the deepest valley quickly and reliably.