More actions
machine learning
supervised learning
- 학습을 시킬 때 label에 정답이 있는 것
- Need input, target
- Learning from difference between prediction and target
- e.g. mnist, classification
unsupervised learning
- label 이 미리 정해져 있지 않은 것
- Need input
- Cluster by distance between inputs
- Can't predict outcome
- e.g. clustering
reinforcement learning
- 일종의 unsupervised learning
- input : environment, reward, output : action
- Learn from try
- Model free
- e.g. game play, stock trading
reinforcement learning
- Q learning
- Neural Network
- DQN : Deep Q Learning
Basic knowledge
- MDP : Markov Decision Process
- Bellman equation
- Dynamic programming
- Value, Polish
- Value function, Polish function
- Value iteration, Polish iteration
실습
numpy, gym, tensorflow 필요
- cartpole_init.py
- cartpole_random.py
- cartpole.py
- cartpole_dqn.pyn
reference
빌표 슬라디으: slide 코드: github
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