Part VIII. Reinforcement Learning Trading Strategy. DQN: QNetwork, QRNNNetwork
This is the part VIII of the Deep Learning Trading Strategy from the beginning to the production series.
In this video we are going to explore the training steps of reinforcement learning agent. We will have a brief description of Q-Learning and DQN, create a DQN agent with QNetwork and QRNNNetwork, and evaluate them.
00:10 Introduction.
00:26 Update of environment.
01:24 Q-Learning
03:03 DQN
04:23 Common steps in training of RL agents
04:55 TF-Agents Q-Network
05:32 TF-Agents Q-RNN-Network
05:43 Create DQN TF-Agent
06:15 Data Collection
06:59 Data Collection (DynamicEpisodeDriver)
07:27 Reply Buffer
07:53 Training of the agent
08:39 Evaluation
08:50 Test results of QNetwork and QRNNNEtwork
Previous video of the series: • Part VII. Reinforcement Learning. Tra...
TF-Agent Environment tutorial: https://www.tensorflow.org/agents/ove...
Git-Hub code from the video: https://github.com/CloseToAlgoTrading...
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