“2016 Summer Seminar for Machine learning”版本间的差异

来自cslt Wiki
跳转至: 导航搜索
第8行: 第8行:
 
| 2016/07/04  ||Dong Wang  || Machine learning overview || [http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution]
 
| 2016/07/04  ||Dong Wang  || Machine learning overview || [http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution]
 
|-
 
|-
| 2016/07/05  ||Dong Wang  || Linear models || [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture]
+
| 2016/07/05  ||Dong Wang  || Linear models || [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf AG's lecture 2]
 
|-
 
|-
 
| 2016/07/    ||Dong Wang  || Neural networks ||  
 
| 2016/07/    ||Dong Wang  || Neural networks ||  

2016年7月3日 (日) 14:00的版本

  • Location: FIT-1-304


Date Speaker Title Materials
2016/07/04 Dong Wang Machine learning overview Algebra review probability review Gaussian distribution
2016/07/05 Dong Wang Linear models NG's lecture 1 AG's lecture 2
2016/07/ Dong Wang Neural networks
2016/07/ Dong Wang Deep learning (1)
2016/07/ Dong Wang Deep learning (2)
2016/07/ Caixia Wang Kernel methods
2016/07/ Dong Wang Probabilistic learning theory
2016/07/ Yang Feng Graphical model: Bayesian approach
2016/07/ Yang Feng Graphical model: Random field
2016/07/ Dong Wang Unsupervised learning
2016/07/ Dong Wang No parametric models Gaussian process
2016/07/ Dong Wang Reinforcement learning
2016/07/ Maoning Wang Evolutionary learning
2016/07/ Dong Wang Optimization Convex optimization I Convex optimization II