Some implementation magic.
The main aim of conv op is to extract useful features for downstream tasks. And different filters could intuitionally extract different aspect of features via backprop during training. Afterward, all the extracted features are combined to make decisions.
The mathematical foundations of policy gradient algorithms.
A summary of sorting algorithms.
A summary of key advances of Deep Q-Networks.
Activation functions lead to non-linearity in neural networks. Most common types are Sigmoid, Tanh, Relu, etc.