Which of the following statement(s) is / are true for Gradient Descent (GD) and Stochastic Gradient Descent (SGD)?

1. In GD and SGD, you update a set of parameters in an iterative manner to minimize the error function.
2. In SGD, you must run through all the samples in your training set for a single parameter update in each iteration.
3. In GD, you either use the entire data points or a subset of training data to update a parameter in each iteration.