The Real Deal About Synthetic Data /

It's often difficult to access the real-world data needed to train models or gain insights, due to privacy and security concerns or simply process issues. However, new AI techniques for generating look-alike data sets can help data scientists develop machine learning models more quickly and at...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Lucini, Fernando (Author)
Corporate Author: Safari, an O'Reilly Media Company
Format: Electronic eBook
Language:Inglés
Published: MIT Sloan Management Review, 2021.
Edition:1st edition.
Subjects:
Artificial intelligence > Data processing.
Machine learning.
Intelligence artificielle > Informatique.
Apprentissage automatique.
Online Access:Texto completo (Requiere registro previo con correo institucional)
Description
Summary:It's often difficult to access the real-world data needed to train models or gain insights, due to privacy and security concerns or simply process issues. However, new AI techniques for generating look-alike data sets can help data scientists develop machine learning models more quickly and at greater scale. This article explains the concept of synthetic data and outlines the benefits and concerns that executives should consider.
Physical Description:1 online resource (6 pages)

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