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Added MIT 6.868J course and fix a little mistake
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Prakhar Srivastav 2016-01-26 08:28:55 -05:00
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@ -557,13 +557,18 @@ Topics covered include probability theory and Bayesian inference; univariate dis
- [Lectures and Assignments](https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/courseware/7206c57866504e83821d00b5d3f80793/)
- [**Machine Learning: 2014-2015**](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/) *University of Oxford* <img src="https://assets-cdn.github.com/images/icons/emoji/unicode/1f4f9.png" width="20" height="20" alt="Lecture Videos" title="Lecture Videos" /> <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/1f4bb.png" width="20" height="20" alt="Assignments" title="Assignments" />
- The course focusses on neural networks and uses the [Torch](https://github.com/torch/torch7/wiki/Cheatsheet) deep learning library (implemented in Lua) for exercises and assignments. Topics include: logistic regression, back-propagation, convolutional neural networks, max-margin learning, siamese networks, recurrent neural networks, LSTMs, hand-writing with recurrent neural networks, variational autoencoders and image generation and reinforcement learning
- [Lecutures and Assignments](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
- [Lectures and Assignments](https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/)
- [Source code](https://github.com/oxford-cs-ml-2015/)
- [EECS E6894](http://llcao.net/cu-deeplearning15/index.html) **Deep Learning for Computer Vision and Natural Language Processing** *Columbia 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/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" />
- This graduate level research class focuses on deep learning techniques for vision and natural language processing problems. It gives an overview of the various deep learning models and techniques, and surveys recent advances in the related fields. This course uses Theano as the main programminging tool. GPU programming experiences are preferred although not required. Frequent paper presentations and a heavy programming workload are expected.
- [Readings](http://llcao.net/cu-deeplearning15/reading.html)
- [Assignments](http://llcao.net/cu-deeplearning15/programming_problem.html)
- [Lecture Notes](http://llcao.net/cu-deeplearning15/index.html)
- [Lecture Notes](http://llcao.net/cu-deeplearning15/index.html)
- [6.868J](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/index.htm) **The Society of Mind** *MIT* <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/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" />
- This course is an introduction, by Prof. [Marvin Minsky](http://www.nytimes.com/2016/01/26/business/marvin-minsky-pioneer-in-artificial-intelligence-dies-at-88.html?_r=0), to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality. It incorporates ideas from psychology, artificial intelligence, and computer science to resolve theoretical issues such as wholes vs. parts, structural vs. functional descriptions, declarative vs. procedural representations, symbolic vs. connectionist models, and logical vs. common-sense theories of learning.
- [Lectures](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/video-lectures/)
- [Assignments](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/assignments/)
- [Readings](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-868j-the-society-of-mind-fall-2011/readings/)
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