As per the paper , you can choose arbitrary distributions , construct a fluent graph , run Monte Carlo simulation and get the result - |via http://bit.ly/hnbuzz01 |
11 karma · joined October 27, 2008
As per the paper , you can choose arbitrary distributions , construct a fluent graph , run Monte Carlo simulation and get the result - |via http://bit.ly/hnbuzz01 |
Try applying it some of the problems you want to solve. Mostly be patient. Unlike conventional programming, machine learning is non deterministic and can take some time to become a little comfortable
http://ocw.mit.edu/courses/electrical-engineering-and-comput...
http://db.cs.berkeley.edu/cs286sp07/
http://www.cs.berkeley.edu/~kubitron/courses/cs194-24-S13/
Its pretty cool. Unfortunately the Linux VM used for development does not exist any more. But Still cool.
If you have the patience, time and the skill needed to comprehend advanced research papers or the time to learn more about machine learning / advanced graphics / distributed systems / compiler optimization and other cool stuff, don't join a Masters Program. If no, may be consider joining a Masters program, you'll not regret <-- but do this only after you have worked for a few years.