04 Aug Reinforcement Learning (II) Actor Critic This is the second note on reinforcement learning focusing on the actor-critic framework 1. RL Technique: Actor-Critic 2. RL Technique: Q-Learning 3. GAN Framework with Actor-Critic PDF Link: Click Here

This is the second note on reinforcement learning focusing on the actor-critic framework 1. RL Technique: Actor-Critic 2. RL Technique: Q-Learning 3. GAN Framework with Actor-Critic PDF Link: Click Here

04 Aug Information Theory This is a note on information theory. Specifically, it is focused on introducing concepts like Entropy, Relative Entropy, Cross Entropy, Maximum Likelihood Estimation for the discrete probability distribution 1. Entropy 2. Relative Entropy 3. Cross Entropy 4. Relation between Entropy, Relative Entropy, and Cross Entropy 5. Maximum Likelihood Estimation 6. MLE and Cross Entropy, Relative Entropy PDF Version: Click Here

This is a note on information theory. Specifically, it is focused on introducing concepts like Entropy, Relative Entropy, Cross Entropy, Maximum Likelihood Estimation for the discrete probability distribution 1. Entropy 2. Relative Entropy 3. Cross Entropy 4. Relation between Entropy, Relative Entropy, and Cross Entropy 5. Maximum Likelihood Estimation 6. MLE and Cross Entropy, Relative Entropy PDF Version: Click Here

27 Jul RNN_MLE Framework This note reviews Recurrent Framework in sequence modeling. 1. RNN-MLE Framework 2. Recurrent Neural Networks (RNN) 3. Gated Recurrent Network (GRU) 4. Long Short Term Memory(LSTM) 5. Maximum Likelihood Framework for Sequence Generation PDF Link: Click Here

This note reviews Recurrent Framework in sequence modeling. 1. RNN-MLE Framework 2. Recurrent Neural Networks (RNN) 3. Gated Recurrent Network (GRU) 4. Long Short Term Memory(LSTM) 5. Maximum Likelihood Framework for Sequence Generation PDF Link: Click Here