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Can Data Mining Algorithms Extract Value from your Personal Data (and should you get a piece of the action?)

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Go to   http://www.datamilk.com/survey/   to have your say. Technology has made it easier than ever for people to collect and store a valuable trove of personal information about themselves. However, there is no readily available means by which individuals can reap a financial benefit by selling their personally generated data. Companies such as Facebook, Linkedin and Twitter are multi-billion dollar companies built almost entirely on user-generated data, so it’s clear that when used correct, your personal data is extremely valuable. There is a growing unease about the disparity between the value that companies realize from personal data and the financial rewards individuals gleam from this information. Prof. Tim Wu from Columbia Law School recently argued that Facebook should pay us for our posts. Individually your data may not be worth very much. but collectibely it is a goldmine. The problem is that there is currently no way for individuals to collect and monetize their
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Beyond the Hype - Data Science in the Real World

I will be presenting this talk at Phil Brieley’s Melbourne Data Science Meetup on June 23 rd . See http://www.meetup.com/Data-Science-Melbourne/events/184731452/ for details. Hope you can join.
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Here is the R code for the competition entry mentioned in my previous post. See http://www.datamilk.com/leaderboard_animation.gif  for the animation. library ( lubridate ) library ( plyr ) library ( sqldf ) library ( ggplot2 ) library ( animation )   #clear everything rm ( list = ls ( all = TRUE ) )   # Injest data data <- read.csv ( "unimelb_public_leaderboard.csv" , header= TRUE )   # calculate days and date time as numeric data <- data.frame ( data , SubmissionDate_datetime = strptime ( data $SubmissionDate , format = "%m/%d/%Y %H:%M:%S %p" ) , Submission_day = round ( strptime ( data $SubmissionDate , format = "%m/%d/%Y %H:%M:%S %p" ) , "day" ) , Submission_time_num = as.numeric ( strptime ( data $SubmissionDate , format = "%m/%d/%Y %H:%M:%S %p" ) ) )   start_time <- min ( na.omit ( data $SubmissionDate_datetime ) ) end_time <- max ( na.omit ( data $SubmissionDate_datetime ) ) s
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Please support me on Kaggle

Hi All I have just entered a Kaggle competition. Please vote for my entry here. https://www.kaggle.com/c/leapfrogging-leaderboards/visualization/886 cheers   Ross Farrelly
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Timeless Classics - the Antidote to Time Poverty

If, like many while collar workers in today’s modern economy, you are “time poor” and constantly swamped by the ever growing torrent of information coming at you every day, despair not. Help is at hand. But is comes in a somewhat unlikely guise. It’s not yet more sophisticated news aggregation text-mining algorithm, nor is it the next-gen web 3.0 nanoblogging, retwetting, facebook posting multifunction one-stop web-accumulation app for your smart phone. No. It is those leather bound volumes gathering dust on your bookshelf and that set of penguin classics you bought in a fit of self-improvement last year and have never read. Let me explain. The idea of being “time poor” really comes down to a balancing our desires. If we want to do more than we have time for, we say we are time poor. There are two possible solutions – either want to do less, or find a way to do more. Focusing on the latter solution, for many professionals, a closely related problem is that of deciding what information
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Review of The Innovator’s Dilemma by Clayton M. Christensen

Main Thesis – Companies need to invest in disruptive technologies, technologies which are typically low spec, more expensive and not required by their current customers in order to stay competitive in the long term. If they don’t, companies which do develop these new technologies will soon develop them into a main stream product which will displace the previous industry standard and the company will not thrive. There is a difference between sustaining innovations, which improve existing ways of doing things, and disruptive technologies, which do things in quite different ways or way a significantly lower cost. Christensen’s findings include: Companies need to invest in disruptive technologies early on.   They usually need to do so by starting a new company or spin off which is solely dedicated to developing the disruptive technology, commercializing it and finding or creating the right market to sell it into. They need to do this because trying to dedicate sufficient r
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Review of Strategic Vision by Zbigniew Brzezinski

I was in the middle of reading Thinking Fast and Slow by Nobel prize winning economist and psychologist Daniel Kahneman which I started reading this book Brzezinski’s Strategic Vision .   One of the findings of Thinking Fast and Slow is that experts have a very, very low success rate when it comes to predicting the future in areas such as politics and economics so I approached Brzezinski’s pronouncements with a skeptical eye.  Nevertheless, in the absence of anything better, it is interesting to see what a foreign policy export like Brzezinski has to say about the future of Europe, America and China. In Part 2 - The Receding West, Brzezinski reminds us that Europe’s woes, both demographic and economic, are well known. Europe lacks the coherence to play a major role on the world stage. Due to its enormous national debt and its involvement in two expensive wars, America also has challenges due to such as: ·          The division between rich and poor in America is widening ·
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