RL notes

This post will contain materials I’ve been using to grasp basic and advanced concepts of Reinforcement Learning.

Neural network basics

  1. Multi-Layer Neural Network -> detailed explanation of feedforward neural network
  2. Understanding LSTMs –> good introduction to recurrent neural network
  3. The Unreasonable Effectivenes of Recurrent Neural Networks –> great blog post to build intuition about RNNs from Andrey Karpathy
  4. ConvNets: A modular perspective –> great blog post about convolutional neural networks
  5. Convolutional Neural Networks, Stanford
  6. Why are ResNets a major breakthrough in Image Processing
  7. Explanation of attention mechanism

RL resources

After presenting relevant resources for Neural netork basics, here I’ll put great RL posts

  1. RL intro –> great lecture for introduction about RL
  2. Deep Reinforcement Learning Doesn’t Work Yet –> very good argumentation about why it’s still not quite feasible to use RL in every occasion

Cool RL papers

  1. Human-level control through deep reinforcement learning