Links

List of some extremely useful online courses,

On Coursera,

• Computational Methods for Data Analysis (Univ of Washington) by Nathan Kutz
• Computational Neuroscience (Univ of Washington) by Rajesh Rao and Adrienne Fairhall
• Control of Mobile Robots (Georgia Tech) by Magnus Egerstedt
• Image and video processing: From Mars to Hollywood with a stop at the hospital (Duke Univ) by Guillermo Sapiro
• Neural Networks for Machine Learning (University of Toronto) by Geoffrey Hinton
• Probabilistic Graphical Models (Stanford) by Daphne Koller
• Machine Learning (Stanford) by Andrew Ng

On Udacity,

• Introduction to Parallel Programming by David Luebke and John Owens
• Artificial Intelligence for Robotics by Sebastian Thrun and Peter Norvig
• Introduction to Artificial Intelligence by Sebastian Thrun and Peter Norvig

On MIT OpenCourseWare,

• MIT 18.06 Linear Algebra by Gilbert Strang

On Stanford's SCPD,

• EE364a: Convex Optimization I by Stephen Boyd
• EE364b: Convex Optimization II by Stephen Boyd
• CS229: Machine Learning by Andrew Ng
• CS228: Probabilistic Graphical Models by Daphne Koller
• Unsupervised Feature Learning and Deep Learning by Andrew Ng

On CMU online,

• 10-701 Machine Learning by Tom Mitchell
• 10-701 Introduction to Machine Learning by Alex Smola
• 10-701x Introduction to Machine Learning by Alex Smola

---

Some URLs "About Me"

• Kaggle
• Google Scholar
• GitHub
• SlideShare
• LinkedIn
• MATLAB Central

or else, above all,
Google me