From ceaa01788cca50471954ebb8daf970f29fa72164 Mon Sep 17 00:00:00 2001 From: Jennifer Shih Date: Thu, 16 Jul 2015 23:42:40 -0700 Subject: [PATCH] added 287 --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index 9438fe5..5b82300 100644 --- a/README.md +++ b/README.md @@ -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* Assignments 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* Lecture NotesReadings - 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/)