Question

Briefly define the following terms using vivid examples:
i. artificial neuron
ii. single layer perceptron
iii. backpropagation
iv. Hopefully Neural Networks.

Answer 1

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1) Artificial Neuron - An artificial neuron is a mathematical function that seeks to simulate the behavior of a biological neuron in the brain/ nerve functions of the brain. Artificial neurons are used to create an artificial neural network – computing system developed to perform actions like one happens inside brain. Artificial Neuron can take 1 or more weighted inputs along with a transformation function and an activation function.Each input is separately weighted.Artificial neuron help computers to think like humans.

eg: Rectifier,Sigmoid etc...

2)  Single layer perceptron - First proposed neural model. Input is multi-dimensional.Input nodes are connected (to a node /multiple nodes in the next layer. The computation of a single layer perceptron is taking sum of product of weights and input vector value. The value which is displayed in the output will be the input of an activation function.

eg: - logistic regression.  

input x = ( I₁, I₂, I₃) = ( 7, 1.2, 2.1 ).

Summed input = = 7w₁ + 1.2 w₂ + 2.1 w₃

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3) Backpropagation - Backpropagation is simply a mechanism by which neural networks learn. It is used to tell whether the net made wrong prediction or not.In backpropagation 3 main steps are there :-

• The network makes a guess about data, using its parameters
• The network is measured with a loss function
• The error is backpropagated to adjust the wrong parameters

The main feature of backpropagation is its iterative, recursive and efficient method for calculating the weights updates to improve the network.

eg: Time-series Prediction

4) Neural Networks - Neural networks are multi-layer networks of neurons that are used to classify things, make predictions, etc.A neural network is a network or circuit of neurons. a neural network is either a biological neural network, made up of real biological neurons, or an artificial neural network.Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns.

eg: clustering , classification , linear regression etc.