Supervised Learning - Classification Week 9 Challenge

1. What is a Neural Network?

sol: Neural networks are a class of machine learning algorithms used to model complex patterns in datasets using multiple hidden layers and non-linear activation functions.

2.What is deep learning?

sol:Deep learning is a type of machine learning, which is a subset of artificial intelligence.deep learning is about computers learning to think using structures modeled on the human brain

3.What is the role of the activation function?

sol: 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?

Binary Step Function.

Linear Activation Function.

Sigmoid/Logistic Activation Function.

The derivative of the Sigmoid Activation Function.

Tanh Function (Hyperbolic Tangent)

Gradient of the Tanh Activation Function.

ReLU Activation Function.The Dying ReLU problem

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.