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updated the CMU ML course

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@ -468,7 +468,7 @@ Courses
- [11-785](http://deeplearning.cs.cmu.edu/) **Deep Learning** *Carnegie Mellon University* <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/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- The course presents the subject through a series of seminars and labs, which will explore it from its early beginnings, and work themselves to some of the state of the art. The seminars will cover the basics of deep learning and the underlying theory, as well as the breadth of application areas to which it has been applied, as well as the latest issues on learning from very large amounts of data. We will concentrate largely, although not entirely, on the connectionist architectures that are most commonly associated with it. *Lectures* and *Reading Notes* are available on the page.
- [15-781](http://www.cs.cmu.edu/~tom/10701_sp11/) **Machine Learning** *Carnegie Mellon University* <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" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- [10-601](http://www.cs.cmu.edu/~ninamf/courses/601sp15/) **Machine Learning** *Carnegie Mellon University* <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" /> <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4da.png" width="20" height="20" alt="Readings" title="Readings" />
- Taught by one of the leading experts on Machine Learning - **Tom Mitchell**
- [Lectures](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml)
- [Project Ideas and Datasets](http://www.cs.cmu.edu/~tom/10701_sp11/proj.shtml)