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Machine learning and privacy

Date of publication: November 10, 2019

Catalogue: Fusion 2019

Company:

Authors: Marcello Frattini, Anna Bellido, Joaquin Casino

Abstract:

Machine Learning algorithms are born as a solution to a problem. Once we feel comfortable with a prototype, there is still a long path to its deployment...and it is rarely a smooth one. We would like to share our experience transiting that path.

Marcello Frattini

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Anna Bellido

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Joaquin Casino

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Machine learning and privacy

Catalogue: Fusion 2019

Author: Anna Bellido

Company: Netquest

November 10, 2019

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Citation

Bellido, A. (2019a, November 10). Machine learning and privacy. ANA - ESOMAR. Retrieved May 24, 2025, from


https://ana.esomar.org/documents/machine-learning-and-privacy-10847


Research Papers

The value of machine learning in privacy

Catalogue: Fusion 2018 (Big Data World + Global Qualitative)

Authors: Carlos Ochoa, Ezequiel Paura

Company: Netquest

November 11, 2018

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Citation

Ochoa and Paura (2018a, November 11). The value of machine learning in privacy. ANA - ESOMAR. Retrieved May 24, 2025, from


https://ana.esomar.org/documents/the-value-of-machine-learning-in-privacy-9493


Videos

The value of machine learning in privacy

Catalogue: Fusion 2018 (Big Data World + Global Qualitative)

Authors: Carlos Ochoa, Ezequiel Paura

Company: Netquest

November 11, 2018

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Citation

Ochoa and Paura (2018a, November 11). The value of machine learning in privacy. ANA - ESOMAR. Retrieved May 24, 2025, from


https://ana.esomar.org/documents/the-value-of-machine-learning-in-privacy


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Citation

Frattini, Bellido and Casino (2019a, November 10). Machine learning and privacy. ANA - ESOMAR. Retrieved May 24, 2025, from


https://ana.esomar.org/documents/the-value-of-machine-learning-in-privacy