Machine Learning 2016 Fall

Course Materials

Powerpoint version of the slides are available here

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