A clear, code-backed walkthrough of bandit algorithms (epsilon-greedy, UCB, Thompson sampling) that maps the exploration/exploitation tradeoff to real problems like ad selection and A/B testing — useful anytime you need to allocate limited trials across uncertain options.
Key quotes
“If you try new places all the time, very likely you are gonna have to eat unpleasant food from time to time.”
