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

2016年7月4日 (一) 09:45的版本

Date	Speaker	Title	Materials
2016/07/04	Dong Wang	Machine learning overview	ppt Algebra review probability review Gaussian distribution Learning theory
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/	Dong Wang	Unsupervised learning
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	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

@@ 第6行： / 第6行： @@
 ! Date !! Speaker!! Title !! Materials
 |-
-| 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][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
+| 2016/07/04  ||Dong Wang  || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning ppt][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][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
 |-
 | 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]