Identify Supervised, Unsupervised, and Reinforcement Learning SNOWPRO-ADVANCED-DATA-SCIENTIST Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   A team is building a model that recommends the best sequence of actions for a robot to navigate a maze. The robot receives a positive reward when it reaches the exit and a negative reward when it hits a wall. Which learning paradigm does this represent?

   • AReinforcement learning
   • BSupervised learning
   • CUnsupervised learning
   • DSemi-supervised learning
   Reveal Solution Discussion Select an answer first
2. 7expert · hard

   A financial trading firm wants to develop an algorithm that learns to execute trades. The algorithm receives market data and must decide whether to buy, sell, or hold. The firm has historical trade data with the profit/loss outcome for each trade, but not the 'optimal' action for each market state. The algorithm will be evaluated on total profit over time. Which learning approach is most appropriate?

   • ASemi-supervised learning with a small labeled set
   • BSupervised learning to predict market movements
   • CReinforcement learning with profit as the reward
   • DUnsupervised learning to cluster market states
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   Which set of characteristics best defines supervised learning?

   • AUses an agent that interacts with an environment to maximize cumulative rewards
   • BUses a reward signal to adjust model parameters without any input features
   • CUses unlabeled data to discover hidden patterns or groupings in the data
   • DUses labeled data to train a model that maps inputs to known outputs
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   What is the primary goal of a supervised learning model?

   • ATo reduce the dimensionality of the input data while preserving variance
   • BTo maximize cumulative reward through interaction with an environment
   • CTo discover natural groupings within unlabeled data
   • DTo learn a mapping from inputs to known output labels
   Reveal Solution Discussion Select an answer first
6. 10application · medium

   A healthcare provider wants to identify groups of patients with similar symptom profiles to discover new subtypes of a disease. The dataset contains patient symptoms but no diagnosis labels. Which learning approach should be used?

   • ASupervised learning with a classifier
   • BReinforcement learning with a reward function
   • CSupervised learning with regression
   • DUnsupervised learning with clustering
   Reveal Solution Discussion Select an answer first