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?

sol:

• 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?

sol: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.