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Rob Aldridge
Works at GCS Agile
Attended Heatherhill High School
Lives in Melbourne, Victoria
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Rob Aldridge

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This insight from BigML highlights the platform's strength in managing “wide” datasets. The platform’s proprietary algorithms scour each feature, no matter how many there are, and identify the features that are most important to the model that you are building.

http://blog.bigml.com/2015/04/28/how-bigml-finds-important-variables-in-wide-datasets/
This blog post is based on a talk I gave at the Dare2Data conference in Madrid. I recently found a fascinating sociology survey with more than 39,000 responses to almost 400 questions. The survey, ...
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Winter is coming and so is the Flu.  The FluTracking.net project is an excellent example where big data is used to help support Public Health.  The project is a joint initiative of Newcastle University, Hunter New England Population Health and the Hunter Medical Research Institute.  The Flutracker is an online health surveillance system which relies on the general public's participation to help detect epidemics of influenza.  All Australian residents (vaccinated or unvaccinated) that have easy access to the internet  on a weekly basis are invited to participate.
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.
#bigdata
http://www.flutracking.net/?inv2f 
An online surveillance system tracking influenza around Australia.
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#machinelearning #artificialintelligence at #amazon

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
Starting in the '90s, Amazon helped show the world how machines can learn. Now it's opening up some of that inside tech to everyone.
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Interesting post. I think many of these visualizations are just pure art, but delivering no insight. So we selected a few of the most powerful ones for you.
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The algorithm that could mean you're never stuck at a red light again. The new algorithm combines city-level data with data on the "mix of vehicles."

"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."
The new MIT system could dramatically cut the amount of time drivers are stuck - and the amount of carbon emission caused by red lights.
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Rob Aldridge

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Starred articles were potential candidates for our picture of the week published in our weekly digest. Enjoy our new selection of articles and resources (R, data science, Python, machine learning etc.) Comments are from Vincent Granville. For a full list of all resources featured so far, click here.
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A very successful and well attended launch of the first Melbourne Data Science Group Breakfast Meet Up.  Great work Elizabeth for helping to co-ordinate this event. Speakers Professor Karin Verspoor and Wayne Palmer.
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In a meeting with Airbus last week I found out that their forthcoming A380-1000 – the supersized airliner capable of carrying up to 1,000 passengers – will be equipped with 10,000 sensors in each wing.
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Really impressive
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Developing machine learning solutions that give a lift from your existing prediction algorithms is not an easy task. They require a multitude of activities to get it right including cleaning up the data, setting up the infrastructure, testing &re-testing the model & finally deploying the algorithm.
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Spitball/Fireball is a Kickstarter project for a machine-learning-based parental monitoring system for smartphones. Spitball is the messaging app for children, and Fireball is the monitoring app for parents. Parents only see messages that have been flagged by the machine learning algorithms as indicating bullying, an online predator, or a suicide risk. Otherwise the children are given privacy.
Spitball is a messaging inbox app for kids. Fireball is the companion app that alerts parents to suspicious messages.
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In his circles
296 people
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364 people
Muhammad Maaz Mughal's profile photo
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Demal Demal's profile photo
Phillip Jarvis's profile photo
Autisable.com's profile photo
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Education
  • Heatherhill High School
    1991
  • Monash University
    Applied Science, 1991 - 1995
    Computer Science, Physics, Machine Vision
Basic Information
Gender
Male
Other names
Robert
Work
Occupation
Solution Architect
Employment
  • GCS Agile
    Practice Lead, 2014 - present
  • Artis Group
    Technical Lead, 2013 - 2014
  • Praxa Limited
    Senior Consultant, 2008 - 2013
Places
Map of the places this user has livedMap of the places this user has livedMap of the places this user has lived
Currently
Melbourne, Victoria
Previously
Chennai
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