Assertion: gradient descent | /r/HasProperty | simple method
Facets:
value: very
type: DEGREE
Source sentences:
text: Gradient descent is a very simple method to implement, and can in theory learn any model with any number of parameters (linear, quadratic, exponential...).
text: Instead, we should apply Stochastic Gradient Descent (SGD), a simple modification to the standard gradient descent algorithm that computes the gradient and updates our weight matrix W on small batches of training data, rather than the entire training set itself.
text: It is a simple and effective method to find the optimum values for the neural network.
text: Gradient descent is a simple optimization procedure that you can use with many machine learning algorithms.