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Deep Learning

Web Ad Optimization (RL)

Solving the Multi-Armed Bandit problem for advertisement clicks using Upper Confidence Bound.

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Web Ad Optimization (RL) screenshot

Project Overview

A Reinforcement Learning project that balances exploration and exploitation to maximize Ad click-through rates.

Technologies Used

PythonReinforcement LearningNumpy

Methodology

  1. 1Simulating a dynamic advertising environment.
  2. 2Implementing the UCB mathematical formula.
  3. 3Updating confidence intervals in real-time.
  4. 4Comparing UCB performance against random selection.

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