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Kiran Kuppa

Machine Learning Video Library - Learning From Data (Abu-Mostafa) - 0 views

work.caltech.edu/...index.html

machine networks statistics learning video lectures

shared by Kiran Kuppa on 30 Jan 13 - No Cached
  • Kiran Kuppa on 30 Jan 13
     
    These are a set of video lectures by Prof. Yaser S. Abu Mostafa of Caltech on Statistical Learning Theory that accompany his book "Learning from Data". The topics covered in brief are: 1.Bayesian Learning 2. Bin Model 3. Data Snooping 4. Ensemble Learning 5. Gradient Descent 6. Learning Curves (Regression) 7. Neural Networks 8. Overfitting problem 9. Radial basis functions and Regularization 10. Support Vector Machines 11. VC Dimension
Benno Hansen

The Economist explains: How might your choice of browser affect your job prospects? | T... - 0 views

www.economist.com/...-browser-affects-job-prospects

browser job statistics data

shared by Benno Hansen on 12 Apr 13 - No Cached
  • applicants who have bothered to install new web browsers on their computers (such as Mozilla's Firefox or Google's Chrome) perform better and stay in their posts for 15% longer, on average, than those who use the default pre-installed browser that came with their machine (ie, Internet Explorer on a Windows PC and Safari on an Apple Mac)
  • applicants who belonged to one or two online social networks tended to stay in their jobs for longer than those who belonged to four or more social networks
Benno Hansen

Media Companies Must Become Trusted Data Hubs » Article » OWNI.eu, Digital Jo... - 0 views

owni.eu/...s-catering-to-the-trust-market

media journalism data

shared by Benno Hansen on 23 Mar 11 - No Cached
  • Advertising and journalism do not complement each other the way they used to.
  • successful media companies of the future have to build an infrastructure that turns them into reliable data hubs, able to analyze even very large and complex datasets internally and to build stories on their insights
  • machine can assemble large portions of articles through structured data
  • ...10 more annotations...
  • computers are getting ever closer to mastering the subtleties of human communication
  • Any event can be described by fundamental data: latitude, longitude, time and date and importance.
  • the fundamental role of journalism will remain the same: searching for truth, and demanding accountability of those in power
  • the majority of online journalists are stuck working with outdated or unimaginative tools
  • Trust, not information, is the scarce resource in today’s world. Trust is something that is hard to earn and easy to lose. And it is a core element of journalism
  • The trust market is still up for grabs. Most media players are still competing in the “attention market.”
  • fact collection will be organized rather than done by journalists
  • In the future, many journalists will resemble project managers, aggregating resources around platforms like Ushahidi rather than dashing adventurers
  • In an era where more and more users have a camera phone and a way to put that content online, the journalist becomes the one who’s best able to curate and validate material from the data deluge, not just adding to it. Crowdsourcing should allow media organizations to devote more resources to vetting information produced by others, and thereby gaining trust.
  • Many investigations will be led behind a computer as journalists organize a community of users and a team of developers to get stories out.
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