Name some basic objects in a neural network and describe their purposes. Why is it called a "neural network"?
We typically say that a neural network "learns". Mathematically, what is "learning" in the context of neural networks?
The output layer of a lot of neural networks are probabilities. For example, the final layer will output a 49.9999% chance of "yes" and 50.0001% chance of "no". Since "no" is more likely, the network will output "no". Give an example in your own field where a network with these percentages might make you think twice about using the output from the network.