Complete Question Index

Browse through all 1416 practice questions (Page 6 of 10)

Essentials • Web Technologies

jQuery is a JavaScript Object Notation library

Essentials • Web Technologies

Some people don’t want animation to interfere with their web page experience. What do I do if I want to let a user turn off the animation?

Essentials • Web Technologies

Raju wants to remove an event handler that was attached with on() function.Help him to select the correct option.

Essentials • Web Technologies

Rhita wants to replace a jQuery code '$(document).ready(fun)' using another equivalent method. Help her to find the correct method from the given opti...

Essentials • Web Technologies

$("#name").remove(); This will remove the text field when you click on the button. State true or false.

Essentials • Web Technologies

Bind an event handler to the "blur" JavaScript event on an element.

Essentials • Web Technologies

When referencing an HTML element using jQuery preceded by a ‘ # ‘ , what JavaScript function is this equivalent to?

Essentials • Web Technologies

The following elements are newly added elements in HTML5: <section> <article> <aside>

Essentials • Web Technologies

Which of the following is most appropriate tag in html 5 to divide the document into logical document groups?

Essentials • Web Technologies

If you want to change the color of a link to red when moving mouse pointer on top of it, which CSS property you need to change?

Essentials • Web Technologies

Which of the following is/are true about HTML?

Essentials • Web Technologies

What is the output of the below code snippet <script type="text/javascript"> amt=55+"55"; document.write(amt); </script>

Essentials • Web Technologies

Choose the correct JavaScript statement which helps you to write "World of JavaScript" in a web page?

Essentials • Web Technologies

Which of the below is the correct syntax for exectuing some code if "amt" is equal to 5000?

Essentials • Web Technologies

Ram is the developer of Allen Software company. He is designing the website for the banking application. There is a button called 'check interest rate...

Essentials • Web Technologies

The parseInt() method converts the string to a integer. Before applying this function, Ram wants to know the type of the argument that is passed to th...

Essentials • Web Technologies

Polson is allocated with the task of email validation in java script. He needs to extract character by character and check for email validation like l...

Essentials • Web Technologies

Predict the output of the following JavaScript code: <html> <head> <script> var txt= "pass 70% fail 30%"; var pattern = /\D/g; var res= txt.matc...

Essentials • Web Technologies

Sita wishes to greet the user when the user clicks on "Greet Me" button. In which event does she need to write the JavaScript code for greeting the us...

Essentials • Web Technologies

Which of the below java script code helps to change the content of the paragraph tag dynamically? <p id="pid1">Aim Higher.. Sky is your limit

Essentials • Web Technologies

Which of the below statements are used to comment a line in JavaScript file?

Essentials • Web Technologies

When a user views a page containing a JavaScript program, which machine actually executes the script?

Essentials • Web Technologies

When you want to enclose; some JavaScript statements to an HTML file, which is the correct tag you have to use?

Essentials • Web Technologies

David, a beginner in web development trying to perform one particular operation using client side JavaScript. Choose the correct option(s) that he c...

Generative AI • Part 1 — Introduction to Generative AI

Generative AI primarily aims to:

Generative AI • Part 1 — Introduction to Generative AI

Which of these is NOT typically produced by generative models?

Generative AI • Part 1 — Introduction to Generative AI

Learning a data distribution p(x) allows a model to:

Generative AI • Part 1 — Introduction to Generative AI

Which statement best contrasts discriminative and generative models?

Generative AI • Part 1 — Introduction to Generative AI

Which is a common application of generative AI?

Generative AI • Part 1 — Introduction to Generative AI

Generative AI that helps artists by suggesting concepts is an example of:

Generative AI • Part 1 — Introduction to Generative AI

A model that learns to produce plausible human faces has learned approximations of:

Generative AI • Part 1 — Introduction to Generative AI

Which capability is NOT typical of generative models?

Generative AI • Part 1 — Introduction to Generative AI

Which of the following is a risk specifically mentioned for generative AI?

Generative AI • Part 1 — Introduction to Generative AI

Text generation, image generation and music generation are examples of:

Generative AI • Part 1 — Introduction to Generative AI

Why is learning a distribution more powerful than memorizing examples?

Generative AI • Part 1 — Introduction to Generative AI

Which of these is a direct benefit of synthetic data?

Generative AI • Part 1 — Introduction to Generative AI

A generative model that outputs new molecules would be used in:

Generative AI • Part 1 — Introduction to Generative AI

Which term best describes creating content that resembles training data but is not identical?

Generative AI • Part 1 — Introduction to Generative AI

Generative AI differs from classification because it focuses on:

Generative AI • Part 2 — History & Foundations

Gaussian Mixture Models (GMMs) are examples of:

Generative AI • Part 2 — History & Foundations

Hidden Markov Models (HMMs) are especially useful for:

Generative AI • Part 2 — History & Foundations

Which breakthrough enabled deep generative models to scale in the 2010s?

Generative AI • Part 2 — History & Foundations

The VAE paper was published by:

Generative AI • Part 2 — History & Foundations

GANs introduced the idea of:

Generative AI • Part 2 — History & Foundations

“Attention Is All You Need” introduced:

Generative AI • Part 2 — History & Foundations

Which year is commonly associated with the original GAN paper?

Generative AI • Part 2 — History & Foundations

Transformers replaced recurrence with:

Generative AI • Part 2 — History & Foundations

Which early model is probabilistic and explicitly models density?

Generative AI • Part 2 — History & Foundations

VAEs are celebrated for:

Generative AI • Part 2 — History & Foundations

Which model family is known as “implicit density”?

Generative AI • Part 2 — History & Foundations

The rise of LLMs was enabled by:

Generative AI • Part 2 — History & Foundations

Which contribution is attributed to Goodfellow et al.?

Generative AI • Part 2 — History & Foundations

CycleGAN is notable because it can:

Generative AI • Part 2 — History & Foundations

Which development made sampling from complex distributions more practical?

Generative AI • Part 3 — ML & Neural Network Fundamentals

Machine Learning systems typically start with:

Generative AI • Part 3 — ML & Neural Network Fundamentals

A perceptron computes:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Which activation is most used to mitigate vanishing gradients?

Generative AI • Part 3 — ML & Neural Network Fundamentals

Backpropagation uses which calculus tool to compute gradients?

Generative AI • Part 3 — ML & Neural Network Fundamentals

Gradient descent updates weights to:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Deep networks learn hierarchical features—early layers learn:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Overfitting happens when the model:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Which is NOT an optimizer for neural networks?

Generative AI • Part 3 — ML & Neural Network Fundamentals

Dropout is used to:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Cross-entropy loss is most often used for:

Generative AI • Part 3 — ML & Neural Network Fundamentals

A bias term in a neuron is analogous to:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Batch normalization primarily helps by:

Generative AI • Part 3 — ML & Neural Network Fundamentals

Which layer type is most common in image models?

Generative AI • Part 3 — ML & Neural Network Fundamentals

Transfer learning helps when:

Generative AI • Part 3 — ML & Neural Network Fundamentals

An epoch means:

Generative AI • Part 4 — Generative Model Taxonomy

Explicit density models provide:

Generative AI • Part 4 — Generative Model Taxonomy

Normalizing Flows are an example of:

Generative AI • Part 4 — Generative Model Taxonomy

Which model family does a VAE belong to?

Generative AI • Part 4 — Generative Model Taxonomy

Implicit models are characterized by:

Generative AI • Part 4 — Generative Model Taxonomy

Which is a tractable explicit model?

Generative AI • Part 4 — Generative Model Taxonomy

Which approach approximates likelihoods using ELBO?

Generative AI • Part 4 — Generative Model Taxonomy

Sampling from an implicit model requires:

Generative AI • Part 4 — Generative Model Taxonomy

Which model gives exact likelihoods (when tractable)?

Generative AI • Part 4 — Generative Model Taxonomy

Which is an advantage of explicit density models?

Generative AI • Part 4 — Generative Model Taxonomy

An example of implicit modeling is:

Generative AI • Part 4 — Generative Model Taxonomy

Which family is well-suited to likelihood-based anomaly detection?

Generative AI • Part 4 — Generative Model Taxonomy

ELBO stands for:

Generative AI • Part 4 — Generative Model Taxonomy

Which is a limitation of implicit models?

Generative AI • Part 4 — Generative Model Taxonomy

Tractable models are useful because they allow:

Generative AI • Part 4 — Generative Model Taxonomy

VAEs, GANs and Flows are examples of:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

A standard autoencoder differs from a VAE because a VAE:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

The reparameterization trick allows:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

VAE loss includes reconstruction loss plus:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

Sampling z = μ + σ ⊙ ε moves randomness to:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

A common prior used in VAEs is:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

VAEs typically produce images that are:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

KL term in VAE encourages:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

Advantages of VAEs include:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

Which is a limitation of VAEs?

Generative AI • Part 5 — Variational Autoencoders (VAEs)

In VAEs, the decoder maps from:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

ELBO maximization is equivalent to:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

Choosing a too-large KL weight will typically:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

VAEs are useful for:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

A well-structured latent space allows:

Generative AI • Part 5 — Variational Autoencoders (VAEs)

Which is true about VAE encoder output?

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

GANs train by:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

Mode collapse means the generator:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

If discriminator becomes too strong early, the generator may suffer from:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

DCGAN stands for a GAN variant optimized for:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

StyleGAN introduced:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

CycleGAN is primarily used for:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

The generator maps noise z to:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

Adversarial loss tries to make discriminator output for generated samples:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

A typical fix for mode collapse is:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

GANs are categorized as:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

Which is a common component of GAN training to stabilize it?

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

Which GAN variant gives control over style at multiple scales?

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

Discriminator\'s role is to:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

GAN training objective is best described as:

Generative AI • Part 6 — Generative Adversarial Networks (GANs)

A challenge when training GANs is:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

RNNs maintain memory via:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Vanishing gradient makes it hard to learn:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

LSTM introduces which mechanism to control information?

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

GRU differs from LSTM by:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Sequence generation can be performed by training models to predict:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Teacher forcing is a training technique where:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Which is a limitation of RNNs compared to Transformers?

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

RNN backpropagation through time requires:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Applications of sequence models include:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Beam search is used in generation to:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Scheduled sampling mixes:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

An RNN cell output depends on:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Which cell is computationally lighter?

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Sequence-to-sequence (seq2seq) models typically have:

Generative AI • Part 7 — Sequence Models (RNN/LSTM/GRU)

Teacher forcing can lead to:

Generative AI • Part 8 — Transformers & Attention

Self-attention allows tokens to:

Generative AI • Part 8 — Transformers & Attention

Positional encoding provides:

Generative AI • Part 8 — Transformers & Attention

Multi-head attention helps by:

Generative AI • Part 8 — Transformers & Attention

Transformers are more parallelizable than RNNs because:

Generative AI • Part 8 — Transformers & Attention

Decoder-only models like GPT are trained to:

Generative AI • Part 8 — Transformers & Attention

BERT is primarily used for:

Generative AI • Part 8 — Transformers & Attention

Transformer encoder blocks include:

Generative AI • Part 8 — Transformers & Attention

Masked self-attention prevents a token from attending to:

Generative AI • Part 8 — Transformers & Attention

Scaling transformers (more params + data) led to:

Generative AI • Part 8 — Transformers & Attention

A positional encoding can be:

Generative AI • Part 8 — Transformers & Attention

Which model is decoder-only?

Generative AI • Part 8 — Transformers & Attention

Attention scores are computed from queries, keys and values using:

Generative AI • Part 8 — Transformers & Attention

Transformer attention is typically multi-head to:

Generative AI • Part 8 — Transformers & Attention

Encoder-decoder transformers are commonly used for:

Generative AI • Part 8 — Transformers & Attention

Which is an advantage of Transformers over RNNs?

Generative AI • Part 9 — Applications, Ethics & Future

Generative AI in healthcare can help by:

Generative AI • Part 9 — Applications, Ethics & Future

In drug discovery generative models can:

Generative AI • Part 9 — Applications, Ethics & Future

A major ethical risk of generative AI is:

Generative AI • Part 9 — Applications, Ethics & Future

Which practice helps reduce model bias?

Generative AI • Part 9 — Applications, Ethics & Future

Copyright concerns arise because models may:

Generative AI • Part 9 — Applications, Ethics & Future

Responsible deployment includes:

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