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When Machine Learning meets Data Privacy

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Manage episode 313294501 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios 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://ppacc.player.fm/legal.

This is the first episode of a podcast series on Machine Learning and Data privacy. Machine Learning is the key to the new revolution in many industries. Nevertheless, ML does not exist without data and a lot of it, which in many cases results in the use of sensitive information. With new privacy regulations, access to data is today harder and much more difficult but, does that mean that ML and Data Science has its days counted? Will the Machines beat privacy?
Don’t forget to subscribe to the mlops.community slack (https://go.mlops.community/slack) and to give a star to the Synthetic data open-source repo (https://github.com/ydataai/ydata-synt...)
Useful links:
Medium post with the podcast transcription - https://medium.com/@fabiana_clemente/...
In case you’re curious about GDPR fines - enforcementtracker.com
The Netflix Prize - https://www.nytimes.com/2010/03/13/technology/13netflix.html
Tensorflow privacy - https://github.com/tensorflow/privacy

  continue reading

441 episodes

Artwork

When Machine Learning meets Data Privacy

MLOps.community

56 subscribers

published

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Manage episode 313294501 series 3241972
Content provided by Demetrios. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Demetrios 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://ppacc.player.fm/legal.

This is the first episode of a podcast series on Machine Learning and Data privacy. Machine Learning is the key to the new revolution in many industries. Nevertheless, ML does not exist without data and a lot of it, which in many cases results in the use of sensitive information. With new privacy regulations, access to data is today harder and much more difficult but, does that mean that ML and Data Science has its days counted? Will the Machines beat privacy?
Don’t forget to subscribe to the mlops.community slack (https://go.mlops.community/slack) and to give a star to the Synthetic data open-source repo (https://github.com/ydataai/ydata-synt...)
Useful links:
Medium post with the podcast transcription - https://medium.com/@fabiana_clemente/...
In case you’re curious about GDPR fines - enforcementtracker.com
The Netflix Prize - https://www.nytimes.com/2010/03/13/technology/13netflix.html
Tensorflow privacy - https://github.com/tensorflow/privacy

  continue reading

441 episodes

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