Deep Learning and Natural Language Processing Quiz

What is the main difference between Narrow AI (Weak AI) and General AI (Strong AI)?

• Narrow AI is designed for specific tasks, while General AI can only perform tasks that require human intelligence.

• Narrow AI lacks the ability to generalize, while General AI is limited to specific tasks.

• Narrow AI excels in its designated area but lacks the ability to generalize, while General AI can perform any intellectual task that a human can do.

• Narrow AI can perform any intellectual task that a human can do, while General AI is designed for specific tasks.

What is the purpose of the Activation Function in an Artificial Neural Network?

• To measure the error between the predicted output and the actual target value.

• To adjust the output of each neuron independently of its inputs.

• To specify the function applied to the output of each neuron.

• To calculate the weighted sum of inputs plus the bias.

Which type of neural network architecture is commonly used in Computer Vision tasks?

• Long Short-Term Memory (LSTM)

• Recurrent Neural Network (RNN)

• Gated Recurrent Unit (GRU)

• Convolutional Neural Network (CNN)

What is the main challenge faced in Natural Language Processing related to Sentiment Analysis?

• Syntax and Grammar Variability

• Ambiguity in sentence structure

• Capturing subtle sentiments like sarcasm and irony

• Limited Data and Resources

Which method for representing text involves converting text into numerical vectors using techniques like BoW and TF-IDF?

• Attention Mechanism

• Bag of Words (BoW)

• Word Embeddings

• Term Frequency-Inverse Document Frequency (TF-IDF)

What is the main objective of Explainable Artificial Intelligence (XAI)?

• To identify real data from fake data

• To answer 'wh' questions related to an obtained answer

• To generate realistic data like images

• To compress input data into a condensed representation

What is the function of the Generator in Generative Adversarial Networks (GANs)?

• Learns to create fake data by getting feedback from the Discriminator

• Provides confidence scores or probability estimates with predictions

• Identifies real data from fake data created by the Generator

• Measures the expected cumulative reward of taking a specific action in a particular state

What is the Q-function in Reinforcement Learning?

• A function that measures the expected cumulative reward of taking a specific action in a particular state and following a particular policy thereafter

• A type of reinforcement learning algorithm that combines Q-learning with deep neural networks

• A class of reinforcement learning algorithms that directly optimize the policy of an agent

• A numerical value that indicates the immediate feedback from the environment after the agent takes an action in a particular state

What is the purpose of the Latent Space in Autoencoders?

• Generate new data instances, useful in various creative applications

• Represents a compressed form of the input data created by the encoder

• Reduce storage space while retaining important visual information

• Facilitate natural language processing tasks by extracting meaningful features

What is the role of the Discriminator in Generative Adversarial Networks (GANs)?

• Measures the expected cumulative reward of taking a specific action in a particular state and following a particular policy thereafter

• Learns to create fake data by getting feedback from the Discriminator

• Provides confidence scores or probability estimates with predictions

• Identifies real data from fake data created by the Generator