Powerpoint version of the slides: link
Introduction of this course pdf (2016 /09/23)
Learning Map pdf, video (2016 /09/30)
Regression: Case Study pdf, video (2016 /09/30)
Gradient Descent pdf, video (2016 /10/07)
Where does the error come from? pdf, video (2016 /10/07)
Classification: Probabilistic Generative Model pdf, video (2016 /10/07)
Classification: Logistic Regression pdf,video (2016/10/14)
Brief Introduction of Deep Learning pdf,video (2016/10/14)
Backpropagation pdf,video (2016/10/28)
“Hello world” of deep learning pdf,video(2016/10/28)
Tips for deep learning pdf,video (2016/11/04)
Convolutional Neural Network pdf,video (2016/10/28)
Why deep pdf,video (2016/11/04)
Semi-supervised Learning pdf,video (2016/11/11)
Unsupervised Learning: Linear Dimension Reduction pdf,video (2016/11/11)
Unsupervised Learning: Word Embedding pdf,video (2016/11/25)
Unsupervised Learning: Neighbor Embedding pdf,video (2016/12/02)
Unsupervised Learning: Deep Auto-encoder pdf,video (2016/11/18)
Unsupervised Learning: Deep Generative Model pdf,video (part 1),video (part 2) (2016/12/02)
Final rule,project1,project2,project3 (2016/12/02)
Transfer Learning pdf,video (2016/12/09)
Support Vector Machine (SVM) pdf,video (2016/12/09)
Structured Learning: Introduction pdf,video (2016/12/09)
Structured Learning: Linear Model pdf,video (2016/12/09)
Structured Learning: Structured SVM pdf,video (2016/12/12)
Structured Learning: Sequence Labeling pdf,video (2016/12/23)
Structured Learning: Recurrent Neural Network pdf,video (part 1),video (part 2) (2016/12/30)
Ensemble pdf,video (2016/01/06)
Deep Reinforcement Learning: Scratching the surface pdf,video (2016/01/06)