Applied Deep Learning (2019 Spring) @ NTU
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Updated
Jun 9, 2019 - Jupyter Notebook
Applied Deep Learning (2019 Spring) @ NTU
Training a vision-based agent with the Deep Q Learning Network (DQN) in Atari's Breakout environment, implementation in Tensorflow.
Difficult and annoying Tetris implemented by Reinforcement-Learning
Tensorflow based DQN and PyTorch based DDQN Agent for 'MountainCar-v0' openai-gym environment.
Reinforcement learning framework for implementing custom models on custom environments using state of the art RL algorithms
Optimal drone aeronautical route calculation for making emergency delivery system using drones.
Personal Deep Reinforcement Learning class notes
This project has purpose training an DQN Agent to recognize malware traffic.
Self Driving Car using Deep Q-Learning Networks
Implementation of Deep Recurrent Q-Networks for Partially Observable environment setting in Tensorflow
Dueling Network Architecture Implementation for Deep Reinforcement Learning
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