Machine learning:
423 Matching Annotations
- Oct 2016
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www.theguardian.com www.theguardian.com
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- Sep 2016
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The importance of models may need to be underscored in this age of “big data” and “data mining”. Data, no matter how big, can only tell you what happened in the past. Unless you’re a historian, you actually care about the future — what will happen, what could happen, what would happen if you did this or that. Exploring these questions will always require models. Let’s get over “big data” — it’s time for “big modeling”.
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- Jul 2016
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books.google.ca books.google.ca
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Page 14
Rockwell and Sinclair note that corporations are mining text including our email; as they say here:
more and more of our private textual correspondence is available for large-scale analysis and interpretation. We need to learn more about these methods to be able to think through the ethical, social, and political consequences. The humanities have traditions of engaging with issues of literacy, and big data should be not an exception. How to analyze interpret, and exploit big data are big problems for the humanities.
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journals-openedition-org.accesdistant.sorbonne-universite.fr journals-openedition-org.accesdistant.sorbonne-universite.fr
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big data
les algorithmes ont besoin de données soi-disant neutres.. c'est un peu aller dans le sens des discours d'accompagnement de ces algorithmes et services de recommandation qui considèrent leurs données "naturelles", sans valeur intrasèque. (voir Bonenfant 2015)
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books.google.ca books.google.ca
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Data are not useful in and of themselves. They only have utility if meaning and value can be extracted from them. In other words, it is what is done with data that is important, not simply that they are generated. The whole of science is based on realising meaning and value from data. Making sense of scaled small data and big data poses new challenges. In the case of scaled small data, the challenge is linking together varied datasets to gain new insights and opening up the data to new analytical approaches being used in big data. With respect to big data, the challenge is coping with its abundance and exhaustivity (including sizeable amounts of data with low utility and value), timeliness and dynamism, messiness and uncertainty, high relationality, semi-structured or unstructured nature, and the fact that much of big data is generated with no specific question in mind or is a by-product of another activity. Indeed, until recently, data analysis techniques have primarily been designed to extract insights from scarce, static, clean and poorly relational datasets, scientifically sampled and adhering to strict assumptions (such as independence, stationarity, and normality), and generated and alanysed with a specific question in mind.
Good discussion of the different approaches allowed/required by small v. big data.
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- Jun 2016
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Local file Local file
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After World War II, collaboration became a defin-ing feature of ‘big science’ (Bordons & Gomez, 2000;Cronin, 1995, pp. 4 –13; Katz & Martin, 1997).
collaboration becomes a defining feature of "big science" after the war.
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marco.org marco.org
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Don’t let proprietary podcast platforms convince you that we need them.
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- May 2016
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that doesn't mean the drugs can't be immensely profitable. Treanda is an orphan drug but also Teva's second-best seller, racking up $740 million in sales last year, according to Teva's annual report.
Isn't the whole point of an orphan drug classification that of limited commercial viability? So if they're not commercially viable how are they profitable?
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- Apr 2016
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techcrunch.com techcrunch.com
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We should have control of the algorithms and data that guide our experiences online, and increasingly offline. Under our guidance, they can be powerful personal assistants.
Big business has been very militant about protecting their "intellectual property". Yet they regard every detail of our personal lives as theirs to collect and sell at whim. What a bunch of little darlings they are.
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www.sanders.senate.gov www.sanders.senate.gov
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edtechdigest.wordpress.com edtechdigest.wordpress.com
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The New Politics of Educational Data
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www.nydailynews.com www.nydailynews.com
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Sanders: What I foresee is a stronger national economy. And, in fact, a stronger economy in New York State, as well. What I foresee is a financial system which actually makes affordable loans to small and medium-size businesses. Does not live as an island onto themselves concerned about their own profits. And, in fact, creating incredibly complicated financial tools, which have led us into the worst economic recession in the modern history of the United States.
How does the economy get stronger if more people lose their jobs after this breakup? Has he studied the Bell/Baby Bells divestiture?
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- Mar 2016
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www.jonbecker.net www.jonbecker.net
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Ranty Blog Post about Big Data, Learning Analytics, & Higher Ed
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- Feb 2016
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As Big-Data Companies Come to Teaching, a Pioneer Issues a Warning
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- Jan 2016
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courses.csail.mit.edu courses.csail.mit.edu
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50 Years of Data Science, David Donoho<br> 2015, 41 pages
This paper reviews some ingredients of the current "Data Science moment", including recent commentary about data science in the popular media, and about how/whether Data Science is really di fferent from Statistics.
The now-contemplated fi eld of Data Science amounts to a superset of the fi elds of statistics and machine learning which adds some technology for 'scaling up' to 'big data'.
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news.ubc.ca news.ubc.ca
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Matthew S. MacLennan
I am the author of this paragraph. I am also one of the scientists doing the metabolomic studies. I am in collaboration with many others in this project.
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- Dec 2015
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rainystreets.wikity.cc rainystreets.wikity.cc
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The idea was to pinpoint the doctors prescribing the most pain medication and target them for the company’s marketing onslaught. That the databases couldn’t distinguish between doctors who were prescribing more pain meds because they were seeing more patients with chronic pain or were simply looser with their signatures didn’t matter to Purdue.
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- Sep 2015
- Aug 2015
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www.edudemic.com www.edudemic.com
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Shared information
The “social”, with an embedded emphasis on the data part of knowledge building and a nod to solidarity. Cloud computing does go well with collaboration and spelling out the difference can help lift some confusion.
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europepmc.org europepmc.org
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Big data to knowledge (BD2K)
would like to know more about this term and HHS inititiative
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- Feb 2015
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go.coverity.com go.coverity.com
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the critical role that big data open source projects play in the Internet of Things (IoT).
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- Dec 2014
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www.theatlantic.com www.theatlantic.com
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you’d sound like a pompous jackass.
Holy, leaping jehosaphats of hyperbole, Batman. He's so hyperbolic he's asymptotic. Yeah. I said it.
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