Supervised Learning - Classification Week 9 Challenge

1.What is a Neural Network?
Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input.

2.What is deep learning?
Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.

3.What is the role of the activation function?
activation function is a function that is added into an artificial neural network in order to help the network learn complex patterns in the data.

4.What are the different types of activation functions?
Listed below are some of the types of activation function
Binary Step
Linear
Sigmoid
Tanh
ReLU
Leaky ReLU
Parameterised ReLU
Exponential Linear Unit
Swish
Softmax

5.What do you understand by backpropagation?
Backpropagation is an algorithm used to calculate derivatives quickly. Artificial neural networks use backpropagation as a learning algorithm to compute a gradient descent with respect to weights.The algorithm gets its name because the weights are updated backwards, from output towards input.