Multi armed bandits resources

I am trying to get a better grasp of multi armed bandit algorithms. I have got a decent handle on basic reinforcement learning, and I started reading Bandit Algorithms by Lattimore and but its heavy for me right now. Like way too heavy

Anyone know of some simpler or more intuitive resources to start with? Maybe blog posts, YouTube videos, or lecture notes that explain things like epsilon-greedy, UCB, Thompson Sampling in a more easy way? I saw some nptel courses on youtube but its way too stretched.

Would really appreciate any recs. Thanks!