Participation will help to detect and track both seasonal influenza and hopefully pandemic influenza and other diseases so strategies can be mobilised to better protect the community from epidemics.
New York Times (9 April 2015): "The techniques, called machine learning, are applicable for technology development, finance, bioscience or pretty much anything else that is getting counted and stored online these days. In other words, almost everything." http://bits.blogs.nytimes.com/2015/04/09/amazon-to-sell-predictions-in-cloud-race-against-google-and-microsoft/?_r=0
Wired (9 April 2015): "... the service sounds similar to Microsoft’s Azure Machine Learning Service. But Joseph Sirosh, the Microsoft vice president who oversees Azure Machine Learning and once worked at Amazon, says Microsoft’s service also offers the kind of “deep learning” algorithms that are driving things like Skype’s real-time translation tool or Facebook’s face recognition system."
ZDNet (10 April 2015): "The move by Amazon follows IBM's recent launch of hosted Watson Analytics and Microsoft's Azure Machine Learning, with all three now looking for ways to help developers embed machine learning intelligence into their apps. Google's own machine learning offering, Prediction API, was launched in 2012."
VentureBeat (9 April 2015): "Andy Jassy, the head of the Amazon cloud, spoke about the new service, Amazon Machine Learning, at the 2015 AWS Summit in San Francisco. It’s available today. This is not the most surprising development in the cloud world, considering that Microsoft announced its own similar service, Azure Machine Learning, last June." http://venturebeat.com/2015/04/09/amazon-following-microsoft-introduces-a-cloud-service-for-machine-learning/
Computer World (10 April 2015): "Just last month, for instance, researchers at Carnegie Mellon University and the University of Pittsburgh announced that they are using machine learning to dig through prescription records, genome profiles, insurance records, diagnostic imaging and health records to help create treatment plans for people who not only have the same type of disease but share other similarities, like family history, active lifestyles and age groups." http://www.computerworld.com/article/2908445/aws-offers-machine-learning-service-to-make-sense-of-big-data.html
#AmazonMachineLearning #Google #IBM
"For their test case, Osorio and co author Kanchana Nanduri used simulations of traffic in the Swiss city of Lausanne, simulating the behavior of thousands of vehicles per day, each with specific characteristics and activities. The model even accounts for how driving behavior may change from day to day: For example, changes in signal patterns that make a given route slower may cause people to choose alternative routes on subsequent days."
"'We came up with a solution that would lead to improved travel times across the entire city.' In the case of Lausanne, this entailed modeling 17 key intersections and 12,000 vehicles."
- Heatherhill High School1991
- Monash UniversityApplied Science, 1991 - 1995Computer Science, Physics, Machine Vision
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