"Deep learning DeepLearning core technology in actual combat,"
April 16 - April 19
"deep reinforcement learning core technology in actual combat,"
April 23 - April 26
"Depth Migration learn combat"
May 14 - May 17
a 2. Deep learning overview
2. Deep neural network
3. Convolutional neural network CNN
4. Recurrent neural network RNN
5. Adversarial generation network GAN
6. Reinforcement learning DRL
7. Transfer learning TL
1. Overview of reinforcement learning
2. Markov decision process
3. Monte Carlo method
4. Model-based reinforcement learning
5. Sampling-estimation-based reinforcement learning
6. Reinforcement learning based on approximation theory
7. From reinforcement learning to deep reinforcement Learning
8. Deep Reinforcement Learning
9. Multi-task Deep Reinforcement Learning
10. Hierarchical Deep Reinforcement Learning
11. Multi-agent Reinforcement Learning
1. Unsupervised learning
2. Clustering algorithm
3. Self-supervised learning
4. Transfer learning theory and overview
5. Scenarios suitable for image classification algorithms
6. Scenarios suitable for target detection algorithms
7. Scenarios suitable for image segmentation algorithms
8. 1. Scenarios suitable for natural language processing
9. Scenarios suitable for deep reinforcement learning
10. Scenarios for multi-algorithm hybrid application
Contact: Jet Li (Teacher)
Mobile: 13311241619 Tel: 010-56129268 Official consultation QQ: 1503177939
Reinforcement learning QQ exchange Group number: 872395038 (Add group note: Invited by Jet Li)
Deep learning-distance online course QQ group number: 1057802989 (Add group note: Invited by Jet Li)
Migration learning exchange group number: 879849776 (Add group note: Invited by Jet Li)
