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      Question

      'Reinforcement learning'

      means:
      A Training a model by reinforcing correct predictions with higher weights and incorrect predictions with lower weights in the dataset Correct Answer Incorrect Answer
      B Learning to make decisions by interacting with an environment, receiving rewards for good actions and penalties for bad actions Correct Answer Incorrect Answer
      C A technique for reinforcing underfitted models by adding more training data Correct Answer Incorrect Answer
      D A method of retraining a model each time new data arrives in a streaming pipeline Correct Answer Incorrect Answer
      E A transfer learning approach where a pre-trained model is fine-tuned on a specific task Correct Answer Incorrect Answer

      Solution

      Reinforced Learning components include: • Agent (decision maker) • Environment (what the agent interacts with) • State (current situation) • Action (agent's choice) • Reward (feedback signal) • Policy (agent's strategy) Algorithms include Q-Learning, Deep Q-Network (DQN), Policy Gradient, A3C.  Reinforcement Learning Banking examples include Algorithmic trading (agent learns to buy/sell stocks to maximize portfolio return), Dynamic loan pricing (agent adjusts interest rate offers based on customer behaviour), ATM cash replenishment optimization (agent decides optimal cash loading schedule to minimize both shortfall and excess) and Personalized financial product recommendation systems.

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