Ans:- Neural Network is a supervised machine learning algorithm which is inspired by human nervous system and it replicates the similar to how human brain is trained. It consists of Input Layers, Hidden Layers, & Output Layers.
Neural Networks
1. What is a Neural Network?
2. What are the various types of Neural Networks?
Ans:- Artificial Neural Network, Recurrent Neural Networks, Convolutional Neural Networks, Boltzmann Machine Networks, Hopfield Networks are examples of the Neural Networks. There are a few other types as well.
3. What is the use of activation functions in neural network?
Ans:- Activation function is used to convert a input signal of a node in a A-NN to an output signal. That output signal now is used as a input in the next layer in the stack.
4. What are the different types of activation functions in neural network?
Ans:- Sigmoid or Logistic, Tanh or Hyperbolic tangent, ReLu or Rectified Linear units are examples of activation functions in neural network
5. What is the package name to implement neural network in R?
Ans:- neuralnet package can be used to implement neural network in R
6. What is Cluster Sampling?
Ans :-It is a process of randomly selecting intact groups within a defined population, sharing similar characteristics. Cluster Sample is a probability sample where each sampling unit is a collection or cluster of elements.
