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The Vocabulary of Big Data

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Serii arhivate ("Sursă inactivă" status)

When? This feed was archived on June 16, 2018 02:25 (6+ y ago). Last successful fetch was on April 20, 2018 11:39 (6+ y ago)

Why? Sursă inactivă status. Servele noastre nu au putut să preia o sursă valida de podcast pentru o perioadă îndelungată.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage series 1744869
Content provided by Cambridge University. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Cambridge University or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
Big Data is everywhere, no matter what you do – from humanities to natural sciences, from social sciences to engineering to medicine. Yet, data on its own, no matter how “Big”, is of little use. Distilling Big Data into actionable, useful information requires a range of tools from mathematics, statistics and computer science, which might appear intimidating when approached for the first time. In these talks, we will introduce the key concepts and ideas which underlie modern analysis of large and complex data sets, in a maths-free manner. Image courtesy of François Quévillon from Flickr Creative Commons
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20 episoade

Artwork
iconDistribuie
 

Serii arhivate ("Sursă inactivă" status)

When? This feed was archived on June 16, 2018 02:25 (6+ y ago). Last successful fetch was on April 20, 2018 11:39 (6+ y ago)

Why? Sursă inactivă status. Servele noastre nu au putut să preia o sursă valida de podcast pentru o perioadă îndelungată.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage series 1744869
Content provided by Cambridge University. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Cambridge University or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
Big Data is everywhere, no matter what you do – from humanities to natural sciences, from social sciences to engineering to medicine. Yet, data on its own, no matter how “Big”, is of little use. Distilling Big Data into actionable, useful information requires a range of tools from mathematics, statistics and computer science, which might appear intimidating when approached for the first time. In these talks, we will introduce the key concepts and ideas which underlie modern analysis of large and complex data sets, in a maths-free manner. Image courtesy of François Quévillon from Flickr Creative Commons
  continue reading

20 episoade

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