Neural Networks: Core Concepts Quiz

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Fundamental NN concepts

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Ifat Shaikh

India

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Froggy Jumps Neural Networks: Core Concepts QuizOnline version Fundamental NN concepts by Ifat Shaikh 1 What primarily distinguishes a biological neuron from an artificial neuron? a Biological neurons have no synapses. b Artificial neurons replicate exact brain chemistry. c Biological neurons use electrochemical signaling and complex processing. 2 Which component is central to a perceptron’s decision rule? a Backpropagation error signal b Weighted sum of inputs compared to a threshold c Nonlinear activation of inputs 3 What is the main purpose of backpropagation in multilayer perceptrons? a To initialize weights randomly b To adjust weights by propagating error backward through the network c To forward propagate inputs without updates 4 XOR problem demonstrates what limitation of a single-layer network? a Excessive computational cost b Inability to model non-linear separability c Overfitting with training data 5 Stochastic Gradient Descent differs from batch gradient descent by? a Using the entire dataset for each update b Updating weights per sample or mini-batch c Avoiding any learning rate 6 Which activation function is piecewise linear and widely used in NN? a Tanh b ReLU (Rectified Linear Unit) c Sigmoid 7 Neural networks viewed as directed graphs fall into how many fundamental classes? a Three b Four c Two 8 What characterizes a single-layer feedforward network? a No hidden layer between input and output b Feedback connections from output to input c Multiple hidden layers 9 What defines a multilayer feedforward network? a One or more hidden layers between input and output b Only a single linear layer c Recurrent connections across time 10 Which NN type is designed to handle sequential data with cycles? a Recurrent neural network (RNN) b Multilayer perceptron (MLP) c Convolutional neural network (CNN)

Froggy Jumps

Neural Networks: Core Concepts QuizOnline version

Fundamental NN concepts

by Ifat Shaikh

What primarily distinguishes a biological neuron from an artificial neuron?

Biological neurons have no synapses.

Artificial neurons replicate exact brain chemistry.

Biological neurons use electrochemical signaling and complex processing.

Which component is central to a perceptron’s decision rule?

Backpropagation error signal

Weighted sum of inputs compared to a threshold

Nonlinear activation of inputs

What is the main purpose of backpropagation in multilayer perceptrons?

To initialize weights randomly

To adjust weights by propagating error backward through the network

To forward propagate inputs without updates

XOR problem demonstrates what limitation of a single-layer network?

Excessive computational cost

Inability to model non-linear separability

Overfitting with training data

Stochastic Gradient Descent differs from batch gradient descent by?

Using the entire dataset for each update

Updating weights per sample or mini-batch

Avoiding any learning rate

Which activation function is piecewise linear and widely used in NN?

Tanh

ReLU (Rectified Linear Unit)

Sigmoid

Neural networks viewed as directed graphs fall into how many fundamental classes?

Three

Four

Two

What characterizes a single-layer feedforward network?

No hidden layer between input and output

Feedback connections from output to input

Multiple hidden layers

What defines a multilayer feedforward network?

One or more hidden layers between input and output

Only a single linear layer

Recurrent connections across time

Which NN type is designed to handle sequential data with cycles?

Recurrent neural network (RNN)

Multilayer perceptron (MLP)

Convolutional neural network (CNN)

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Neural Networks: Core Concepts Quiz

Froggy Jumps

About this activity

Created by

Download the paper version to play

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Neural Networks: Core Concepts QuizOnline version

by Ifat Shaikh

What primarily distinguishes a biological neuron from an artificial neuron?

Which component is central to a perceptron’s decision rule?

What is the main purpose of backpropagation in multilayer perceptrons?

XOR problem demonstrates what limitation of a single-layer network?

Stochastic Gradient Descent differs from batch gradient descent by?

Which activation function is piecewise linear and widely used in NN?

Neural networks viewed as directed graphs fall into how many fundamental classes?

What characterizes a single-layer feedforward network?

What defines a multilayer feedforward network?

Which NN type is designed to handle sequential data with cycles?

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