What is perceptron model in artificial neural network? Draw its diagram.

What is the main function of a perceptron in an artificial neural network?<br /> A. 1. To compute a weighted sum of its inputs and apply an activation function to determine the output. <br />B. 2. To reduce the dimensionality of the inputs based on an activation function and learning rate. <br />C. 3. To cluster input data into positive and negative categories, followed by a sigmoid function. <br />D. 4. To optimize the network parameters using gradient descent and backward propagation.

PerceptronPerceptron is Machine Learning algorithm for supervised learning of various binary classificationtasks. Further, Perceptron is also understood as an Artificial Neuron or neural network unit that helpsto detect certain input data computations in business intelligence.Perceptron model is also treated as one of the best and simplest types of Artificial Neural networks.However, it is a supervised learning algorithm of binary classifiers. Hence, we can consider it as asingle-layer neural network with four main parameters, i.e., input values, weights and Bias, net sum,and an activation function. Input Nodes or Input Layer:This is the primary component of Perceptron which accepts the initial data into the system for furtherprocessing. Each input node contains a real numerical value. Wight and Bias:Weight parameter represents the strength of the connection between units. This is another mostimportant parameter of Perceptron components. Weight is directly proportional to the strength of theassociated input neuron in deciding the output. Further, Bias can be considered as the line of interceptin a linear equation. Activation Function:These are the final and important components that help to determine whether the neuron will fire ornot. Activation Function can be considered primarily as a step function.Types of Activation functions: Sign function Step function, and Sigmoid functionThe data scientist uses the activation function to take a subjective decision based on various problemstatements and forms the desired outputs. Activation function may differ (e.g., Sign, Step, and Sigmoid)in perceptron models by checking whether the learning process is slow or has vanishing or explodinggradients

What is a perceptron?Select one:a.A type of machine learning algorithm for classification tasksb.A type of artificial neuron that can be trained to recognize patternsc.A type of deep learning neural networkd.A type of unsupervised learning algorithm

Describe the steps of  Backpropagation  learning algorithm in artificial neural network (ANN)

The behavior of a biological neural network can be captured by a simple model called an artificial neuron or perceptron. Which of the following statements about the perceptron is correct? a. Perceptrons can only be used for linearly separable problems. b. Perceptrons are a type of unsupervised learning algorithm. c. Perceptrons have no activation function. d. Perceptrons can have multiple layers, just like deep neural networks.