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...
| Autores Corporativos: | , |
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| Otros Autores: | |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
MIT Sloan Management Review
2021.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009820376806719 |
| 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. |
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| Descripción Física: | 1 online resource (6 pages) |
