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@@ -9,6 +9,7 @@
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1. [Machine Learning - Stanford](https://class.coursera.org/ml-005) by Andrew Ng in Coursera
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1. [Machine Learning - Stanford](https://class.coursera.org/ml-005) by Andrew Ng in Coursera
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2. [Machine Learning - Caltech](http://work.caltech.edu/lectures.html) by Yaser Abu-Mostafa
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2. [Machine Learning - Caltech](http://work.caltech.edu/lectures.html) by Yaser Abu-Mostafa
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+3. [Machine Learning - Carnegie Mellon](http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml) by Tom Mitchell
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2. [Neural Networks for Machine Learning](https://class.coursera.org/neuralnets-2012-001) by Geoffrey Hinton in Coursera
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2. [Neural Networks for Machine Learning](https://class.coursera.org/neuralnets-2012-001) by Geoffrey Hinton in Coursera
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3. [Neural networks class](https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH) by Hugo Larochelle from Université de Sherbrooke
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3. [Neural networks class](https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH) by Hugo Larochelle from Université de Sherbrooke
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4. [Deep Learning Course](http://cilvr.cs.nyu.edu/doku.php?id=deeplearning:slides:start) by CILVR lab @ NYU
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4. [Deep Learning Course](http://cilvr.cs.nyu.edu/doku.php?id=deeplearning:slides:start) by CILVR lab @ NYU
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@@ -76,3 +77,8 @@
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8. [Fantastic Torch Tutorial](http://code.cogbits.com/wiki/doku.php)
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8. [Fantastic Torch Tutorial](http://code.cogbits.com/wiki/doku.php)
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9. [gfx.js](https://github.com/clementfarabet/gfx.js)
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9. [gfx.js](https://github.com/clementfarabet/gfx.js)
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10. [Torch7 Cheat sheet](https://github.com/torch/torch7/wiki/Cheatsheet)
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10. [Torch7 Cheat sheet](https://github.com/torch/torch7/wiki/Cheatsheet)
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+-----
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+### Contributing
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+Have anything in mind that you think is awesome and would fit in this list? Feel free to send a [pull request](https://github.com/prakhar1989/awesome-courses/pulls).
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