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• Bandit Methods: Bandit methods are a class of online learning algorithms used in reinforcement learning problems where the goal is to maximize the cumulative reward over a sequence of actions. In bandit problems, the agent is faced with a set of actions, e ... Read More >>
• Congestion Hotspots: Congestion hotspots refer to specific locations or areas where traffic congestion is consistently high and causes significant delays for commuters. In the context of data science, congestion hotspots can be identified and analyzed using var ... Read More >>
• Ensemble Methods: Ensemble methods are a set of techniques in machine learning and data science that combine multiple models to improve the overall performance of the system. The idea behind ensemble methods is to leverage the strengths of different models a ... Read More >>