Neural Networks Basics Quiz

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Test NN fundamentals.

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Prajna K B

India

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Froggy Jumps Neural Networks Basics QuizVersión en línea Test NN fundamentals. por Prajna K B 1 What is supervised learning in neural networks? a Learning without a teacher (unsupervised). b Learning with a teacher using labeled input-output pairs. c Learning by trial-and-error without labels. 2 What is reinforcement learning? a Learning with labeled data only. b Agent learns by trial and error to maximize rewards. c Supervised classification with static data. 3 What are the three main NN architectures? a Single-layer feedforward, multilayer feedforward, recurrent. b Convolutional, autoencoder, GAN. c Generative, discriminative, reinforcement. 4 What is a multilayer feedforward network? a A single-layer network. b A network with feedback loops. c A network with one or more hidden layers. 5 What is knowledge representation in NN? a Only weights and biases. b Activation values alone. c Stored information/models used to interpret the world. 6 What is the credit-assignment problem? a Determining which internal decisions contributed to outcomes (temporal/structural). b Assigning hardware credits. c Setting the learning rate. 7 What is a signal-flow graph in NN? a A graph of data distributions. b A graphical representation of signal flow between nodes. c A graph of training losses. 8 What is an activation function? a Weight value. b Bias value. c Non-linear function that introduces non-linearity. 9 What is bias in a neuron? a A learned weight. b A constant added to the weighted sum to shift activation. c An input data point. 10 What is a recurrent network? a A network with at least one feedback loop. b A network with no hidden layers. c A purely feedforward network.

Froggy Jumps

Neural Networks Basics QuizVersión en línea

Test NN fundamentals.

por Prajna K B

What is supervised learning in neural networks?

Learning without a teacher (unsupervised).

Learning with a teacher using labeled input-output pairs.

Learning by trial-and-error without labels.

What is reinforcement learning?

Learning with labeled data only.

Agent learns by trial and error to maximize rewards.

Supervised classification with static data.

What are the three main NN architectures?

Single-layer feedforward, multilayer feedforward, recurrent.

Convolutional, autoencoder, GAN.

Generative, discriminative, reinforcement.

What is a multilayer feedforward network?

A single-layer network.

A network with feedback loops.

A network with one or more hidden layers.

What is knowledge representation in NN?

Only weights and biases.

Activation values alone.

Stored information/models used to interpret the world.

What is the credit-assignment problem?

Determining which internal decisions contributed to outcomes (temporal/structural).

Assigning hardware credits.

Setting the learning rate.

What is a signal-flow graph in NN?

A graph of data distributions.

A graphical representation of signal flow between nodes.

A graph of training losses.

What is an activation function?

Weight value.

Bias value.

Non-linear function that introduces non-linearity.

What is bias in a neuron?

A learned weight.

A constant added to the weighted sum to shift activation.

An input data point.

What is a recurrent network?

A network with at least one feedback loop.

A network with no hidden layers.

A purely feedforward network.

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Neural Networks Basics Quiz

Froggy Jumps

Sobre esta actividad

Creada por

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Froggy Jumps

Neural Networks Basics QuizVersión en línea

por Prajna K B

What is supervised learning in neural networks?

What is reinforcement learning?

What are the three main NN architectures?

What is a multilayer feedforward network?

What is knowledge representation in NN?

What is the credit-assignment problem?

What is a signal-flow graph in NN?

What is an activation function?

What is bias in a neuron?

What is a recurrent network?

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