Other Applications DY0-001 Practice Questions (Page 4)

Questions 16–20

1. 16application · medium

   A social media platform wants to identify influential users who are central to the spread of information. They have a dataset of user interactions (follows, mentions, and shares). Which graph analysis concept is most appropriate for identifying these influential users?

   • ACentrality measures, such as betweenness centrality, which quantify a node's importance in the network.
   • BPathfinding algorithms, such as Dijkstra's algorithm, to find the shortest path between users.
   • CGraph coloring, which assigns colors to nodes to avoid conflicts.
   • DCommunity detection, which groups users into clusters based on their interactions.
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2. 17foundation · easy

   What is the main difference between Q-learning and SARSA?

   • AQ-learning requires a model of the environment, while SARSA does not
   • BQ-learning is off-policy, while SARSA is on-policy
   • CQ-learning is used for regression, while SARSA is used for classification
   • DQ-learning is only for discrete action spaces, while SARSA is for continuous
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4. 18foundation · easy

   Which statement best describes the purpose of graph analysis in data science?

   • ATo analyze data that is organized in rows and columns to find statistical summaries
   • BTo model and analyze relationships between entities to uncover patterns and insights
   • CTo reduce the dimensionality of high-dimensional data while preserving variance
   • DTo convert unstructured text into numerical vectors for machine learning models
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5. 19expert · hard

   A trading firm is developing an automated system to optimize stock trading decisions. The system must balance the trade-off between immediate profit and long-term portfolio growth. The environment is stochastic, and the state space includes the current portfolio value and market indicators. Which reinforcement learning approach is most appropriate for this complex, continuous state space?

   • ADeep Q-Networks (DQN), which use a neural network to approximate the Q-value function for high-dimensional state spaces.
   • BA rule-based system that follows predefined trading rules based on market indicators.
   • CQ-learning with a tabular representation of the state space.
   • DMonte Carlo policy evaluation, which estimates value functions from complete episodes.
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6. 20foundation · easy

   What is the purpose of applying a low-pass filter to a signal?

   • ATo compress the signal for storage
   • BTo remove high-frequency noise from the signal
   • CTo amplify the high-frequency components of the signal
   • DTo convert the signal from analog to digital
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