MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -The Neural Network is constructed from 3 type of layers: Input layer-initial data for the neural network. Hidden layers-intermediate layer between input and output layer and place where all the computation is done. Output layer-produce the result for given inputs.

Detailed explanation-2: -A set of nodes, analogous to neurons, organized in layers. A set of weights representing the connections between each neural network layer and the layer beneath it. The layer beneath may be another neural network layer, or some other kind of layer. A set of biases, one for each node.

Detailed explanation-3: -What Are the Components of a Neural Network? There are three main components: an input later, a processing layer, and an output layer. The inputs may be weighted based on various criteria.

Detailed explanation-4: -There are typically three parts in a neural network: an input layer, with units representing the input fields; one or more hidden layers; and an output layer, with a unit or units representing the target field(s). The units are connected with varying connection strengths (or weights).

Detailed explanation-5: -1.2 Artificial Neural Network Architecture. ANN is made of three layers namely input layer, output layer, and hidden layer/s. There must be a connection from the nodes in the input layer with the nodes in the hidden layer and from each hidden layer node with the nodes of the output layer.