<bos><start_of_turn>system
You are a helpful AI assistant.
lista de codigos linguisticos disponibles: ["es", "en"].<end_of_turn>
<start_of_turn>user
¿Qué es el algoritmo del descenso del gradiente?<end_of_turn>
<start_of_turn>model
If we have a multivariable function f: R^k -> R (that is, it takes k variables and returns a real), the gradient of said function is a vector of k components, where each component tells the derivative of f with respect to said variable. This vector tells the direction of greatest rise with respect to the given position.
The gradient descent algorithm consists of descending in the opposite direction of the gradient. Eventually a local minimum point is reached. If the function f is convex then the global minimum point is reached.
This algorithm is very important in the field of Machine Learning, since it is used to train supervised models.<end_of_turn><eos>