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Showing posts with the label algorithms

The most famous Machine Learning MOOC of our time

If you haven't taken the Stanford's Machine Learning MOOC by Prof Andrew Ng on Coursera, you are less likely to be taken seriously in the AI community. Or so they say. Somewhere in 2008 Andrew Ng started the Stanford Engineering Everywhere (SEE) program that placed a number of Stanford courses online, for free. Andrew himself was responsible for teaching one of these courses, Machine Learning, which consisted of video lectures by him, along with the student materials used in the Stanford CS229 class. The "applied" version of the Stanford class (CS229a) was hosted on and started in October 2011, with over 100,000 students registered for its first iteration; and became one of the first successful MOOCs made by Stanford professors. Andrew Ng and Daphne Koller left Stanford to co-found Coursera in 2012. The Machine Learning course was one of the key offerings on the platform. And it continues to be #1 (check  here ,  here , or comprehensively here

Bubble-Game Theory

YOU CAN CONSIDER GOOGLE your friend only if the two of you play games with each other -- especially with Google the search box. I call our little game Bubble-game. The rule is simple. You need to come up with a vaguely familiar term that you know from somewhere -- desirably from within the Google Apps ecosystem that you personally use on various gadgets. Again, the only rule is that the term should be only vaguely familiar, if at all. It is not necessary to know the precise spelling. So then, you turn to and ask. From within the context of your 'relationship' with Google, the algorithm would suggest to you the possible answers in the form of search results. And depending on how extensively you use Google --or, to put it more socially-- depending on how well Google 'knows' you, you should find traces in the search results that may indicate where you might have encountered the term for the first time and the subsequent info-branches it created thereafter:

George Sugihara On Early Warning Signs

Earlier this month SEED magazine published this very interesting article by George Sugihara, theoretical biologist at Scripps Institution of Oceanography, on how deep mathematical models tie the events of climat change, epileptic seizure, fishery collapses, and risk management surrounding the global financial crisis. Excerpts: [...] Economics is not typically thought of as a global systems problem. Indeed, investment banks are famous for a brand of tunnel vision that focuses risk management at the individual firm level and ignores the difficult and costlier, albeit less frequent, systemic or financial-web problem. Monitoring the ecosystem-like network of firms with interlocking balance sheets is not in the risk manager’s job description. A parallel situation exists in fisheries, where stocks are traditionally managed one species at a time. Alarm over collapsing fish stocks, however, is helping to create the current push for ecosystem-based ocean management. This is a step in the ri