Awesome-Mirrors/awesome-courses
1
0
Fork 0
mirror of https://github.com/prakhar1989/awesome-courses.git synced 2024-10-01 05:45:36 -04:00
Code Issues Packages Projects Releases Wiki Activity

added 287

Browse Source
This commit is contained in:
Jennifer Shih 2015-07-16 23:42:40 -07:00
parent b4370d0ac8
commit ceaa01788c
1 changed files with 4 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@ -507,6 +507,10 @@ Courses
- Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. This course is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. During the 10-week course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision.
- [Lecture Notes](http://cs231n.stanford.edu/syllabus.html)
- [Github Page](http://cs231n.github.io/)
- [CS 287](http://www.cs.berkeley.edu/~pabbeel/cs287-fa13/) **Advanced Robotics** *UC Berkeley* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" />
- The course introduces the math and algorithms underneath state-of-the-art robotic systems. The majority of these techniques are heavily based on probabilistic reasoning and optimization---two areas with wide applicability in modern Artificial Intelligence. An intended side-effect of the course is to generally strengthen your expertise in these two areas.
- [Lectures Notes](http://www.cs.berkeley.edu/~pabbeel/cs287-fa13/#syllabus)
- [Assignments](http://www.cs.berkeley.edu/~pabbeel/cs287-fa13/#assignments)
- [CS 4780](http://www.cs.cornell.edu/courses/CS4780/2014fa/) **Machine Learning** *Cornell University* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4dd.png" width="20" height="20" alt="Lecture Notes" title="Lecture Notes" /><img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- This course will introduce you to technologies for building data-centric information systems on the World Wide Web, show the practical applications of such systems, and discuss their design and their social and policy context by examining cross-cutting issues such as citizen science, data journalism and open government. Course work involves lectures and readings as well as weekly homework assignments, and a semester-long project in which the students demonstrate their expertise in building data-centric Web information systems.
- [Syllabus](http://www.cs.cornell.edu/courses/CS4780/2014fa/)