AI Seminar（目錄）

AI Seminar（目錄）

2019/01/02
 
----- 

-----

大綱：

Part I - Deep Learning
1. Overview,
2. Computer Vision, 3. Fundamental Topics,
4. Natural Language Processing, 5. Graph,
6. Speech, 7. Deep Generative Models, 8. Advanced Topics.

-----

1.3. 30 Topics in Deep Learning
‧Back Propagation

-----

2. CV

-----

3. Fundamental Topics

3.1. Optimization
‧SGD
‧Momemtum
‧NAG
‧AdaGrad
‧AdaDelta
‧RMSProp
‧Adam
‧AdaMax
‧Nadam

3.2 Regularization  
‧Weight Decay
‧Dropout

3.3 Normalization  
‧Batch
‧Weight
‧Layer
‧Instance
‧Group

3.4. Activation Function
‧Sigmoid
‧tanh
‧ReLU
‧LReLU
‧PReLU
‧Softmax
‧ELU

 
3.5. Loss Function

3.6. Back Propagation

-----

4. NLP

4.1. LSTM
4.2. Seq2seq
4.3. Attention
4.4. ConvS2S
4.5. Transformer
4.6. BERT Overview
4.7. Hsitory of Natural Language Processing