网络公开课资源

网络公开课资源

网络公开课资源 ——关注CS/AI/Math

当当当当~请看这个网址 - http://www.class-central.com/ - 它是一个列表，列出几大在线课程网站（有英文字幕和习题就是好啊^^）的课程表 (比网易云课堂更原汁原味哦，现在也可以看课程图谱，学累了可以轻松几分钟 ，还有浙大的计算机中的数学)

Stanford's Coursera - http://www.coursera.org/ Edx - https://www.edx.org

Udacity（也是Stanford教授参与创建的）- http://www.udacity.com/

Caltech(California Institute of Technology) -

http://work.caltech.edu/telecourse.html Machine Learning course, April 3rd till May 31st 2012

这些都是新课，在网上正在上的课。之前的MIT OCW(数学课很厉害，CS在这里)是已经结束了的课，有Multimedia content标志的课值得一听。 这些新课好多都是CS的:

最近刚结束的有Introduction to AI , Introduction to Databases(SQL,OLAP,NoSQL) and Introduction to Machine Learning

正on live的有Probabilistic Graphical Models, Natural Language Processing, Design and Analysis of Algorithms I,CS 101: Building a Search Engine

即将开始的有Introduction to Machine Learning, Learning from Data ( Introductory Machine Learning course),Computer Vision, CS212 - The Design of Computer Programs,

Stanford engineering everywhere - http://see.stanford.edu/see/courses.aspx

artificial intelligence|natural language processing

http://see.stanford.edu/see/lecturelist.aspx?coll=63480b48-8819-4efd-8412-263f1a472f5a 翻译 artificial intelligence|machine learning

http://see.stanford.edu/see/courseinfo.aspx?coll=348ca38a-3a6d-4052-937d-cb017338d7b1 网易翻译版

Some mathematical details and derivations have been omitted in

this course, since this is CS229a - Applied Machine Learning at Stanford. The course with complete Mathematical Depth ( but lesser emphasis on practical application ) is CS229 - Machine Learning. In case you are interested in more algorithms, reinforcement learning and the mathematical derivation for some of the methods, you might find it interesting and useful to take a look at the regular CS229 notes. http://cs229.stanford.edu/materials.html

The problem sets are also mathematical and challenging.

Standford wiki for unsupervised learning

http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial

Harvard university extension school -

http://www.extension.harvard.edu/courses/subject/computer-science

http://www.extension.harvard.edu/open-learning-initiative/math-sets-probability

Machine Learning -Spring 2011

Carnegie Mellon University，大名鼎鼎的 Tom Mitchell

http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml with videos, assignments, exams and solutions (also slides, exercises and exams available for the previous 9 installments of the course).

http://www.cs.cmu.edu/~avrim/ML09/index.html

It's <machine learning theory>, focusing on theoretical aspects of machine learning, I think it may consider as a advanced theory foundation to machine learning course.

Google Code University https://code.google.com/edu/

Python Course(有个Python学习社区) C++ Course