In deep learning models, the activation function refers to a function in an artificial neuron (node) that delivers an output based on inputs. Activation functions in artificial neurons (nodes) are an important part of the role that the artificial neurons (nodes) play in modern artificial neural networks. One of the most popular activation functions for regression tasks is the rectified linear unit, or RELU. Mathematically, the RELU is defined as: x20 a(x) ={ 0. x<0 Write a function called relu(x) that will perform the ReLU activation function on a given vector x. The function should return the output of the activation function. If X- 4:1:3, what is relu(X)?

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Temporal difference learning

Temporal difference learning (TD learning) is a concept in machine learning that attributes to a class of model-free reinforcement learning methods. The technique predicts a reward or quantity depending on the future values of the value function.