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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lucini, Fernando (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico eBook
Idioma:Inglés
Publicado: MIT Sloan Management Review, 2021.
Edición:1st edition.
Temas:
Artificial intelligence > Data processing.
Machine learning.
Intelligence artificielle > Informatique.
Apprentissage automatique.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario: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.
Descripción Física:1 online resource (6 pages)

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