NeuralWaveChallengeOne
Quiz by Karma Frenzoid (MrFrenzoid)
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- Q1What is the vanishing gradient problem in deep learning?Network outputs stop responding to inputGradients become too large and cause instabilityGradients become too small to update weights effectivelyThe learning rate is too high10s
- Q2What is 'gradient clipping' used for in deep learning?To improve model accuracy without retrainingLimit gradients to prevent exploding gradientsTo stop vanishing gradientsTo adjust the weights more aggressively15s
- Q3What does the acronym AI stand for?Artificial InsightAutomated InferenceArtificial IntelligenceAutonomous Intelligence10s
- Q4
What is one of the primary uses of the latent space in autoencoders?
Prediction of future states
Real-time image processing
Data compression and feature extraction
Classification of different classes
15s - Q5USI partners with which Swiss AI research institute?ETH ZurichIDSIACERN AI LabEPFL AI Lab10s
- Q6
Latent spaces are often used in which type of neural networks?
Autoencoders and Variational Autoencoders
Feedforward Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
15s - Q7
In deep learning, what is the purpose of using a dropout layer in neural networks?
To reduce overfitting by randomly disabling channels between neurons during training.
To increase the network’s training speed
To improve the network’s accuracy by retraining only specific layers.
To prevent vanishing gradients by reconnecting neurons to their previous layers.
15s - Q8Who is the inventor of LSTMs?Orion PaxAlan TuringJürgen SchmidhuberSophie Germain10s
- Q9In Generative Adversarial Networks (GANs), what is the role of the discriminator?To distinguish between real and artificially generated dataTo adjust the learning rateTo backpropagate gradients through the networkTo generate new data10s
- Q10
Which of the following best describes the Bellman equation in reinforcement learning?
It defines the reward function for decision-making.
It provides a recursive definition for the value of a state.
It predicts future actions based on historical data.
It measures the accuracy of model predictions.
15s - Q11
In natural language processing, the “BERT” model differs from earlier models because it
Predicts missing words in sentences using a bidirectional context
Relies on RNN-based recurrent layers to capture word order
Focuses solely on phonetic patterns in the language
Uses only a unidirectional context to predict the next word in a sequence
15s - Q12
In adversarial machine learning, which technique is used to fool a model into making incorrect predictions?
Dropout
Adversarial Perturbations
Regularization
Data Augmentations
15s - Q13
In the realm of neural network architectures, what is the primary purpose of a "Capsule Network" as introduced by Geoffrey Hinton?
To implement reinforcement learning within convolutional architectures for better decision-making processes.
To enable the network to recognize spatial hierarchies and relationships between features more effectively than traditional CNNs.
To incorporate quantum computing principles into neural networks for enhanced processing speeds.
To reduce the computational complexity of deep networks by using capsule layers instead of traditional convolutional layers.
30s - Q14
What is the 10th decimal of Pi
3
5
9
4
15s - Q15
In a recurrent neural network (RNN), which of the following issues is commonly encountered when dealing with long sequences?
Complex feature extraction
Weight underfitting
Vanishing and Exploding Gradients
Gradient Saturation
15s