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Using AutoML to automate selection of machine learning models and hyperparameters /
"Automated machine learning (AutoML) enables both data scientists and domain experts (with limited machine learning training) to be productive and efficient. In recent years, AutoML has fostered a fundamental shift in how organizations approach machine learning, making it more accessible to bot...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Formato: | Electrónico Congresos, conferencias Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
O'Reilly,
2019.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Lazzeri, Francesca, |e on-screen presenter. | |
| 245 | 1 | 0 | |a Using AutoML to automate selection of machine learning models and hyperparameters / |c Francesca Lazzeri, Wee Hyong Tok. |
| 246 | 3 | |a Using Auto Machine Learning to automate selection of machine learning models and hyperparameters | |
| 264 | 1 | |a [Place of publication not identified] : |b O'Reilly, |c 2019. | |
| 300 | |a 1 online resource (1 streaming video file (42 min., 33 sec.)) | ||
| 336 | |a two-dimensional moving image |b tdi |2 rdacontent | ||
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| 337 | |a video |b v |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Title from title screen (viewed November 14, 2019). | ||
| 518 | |a Recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York. | ||
| 511 | 0 | |a Presenters, Francesca Lazzeri, Wee Hyong Tok. | |
| 520 | |a "Automated machine learning (AutoML) enables both data scientists and domain experts (with limited machine learning training) to be productive and efficient. In recent years, AutoML has fostered a fundamental shift in how organizations approach machine learning, making it more accessible to both experts and nonexperts. Most real-world data science projects are time-consuming, resource intensive, and challenging. Besides data preparation, data cleaning, and feature engineering, data scientists often spend a significant amount of time on model selection and tuning of hyperparameters. Automated machine learning changes that, making it easier to build and use machine learning models in the real world. Francesca Lazzeri and Wee Hyong Tok (Microsoft) lead a gentle introduction to how AutoML works and the state-of-art AutoML capabilities that are available. You'll learn how to use AutoML to automate selection of machine learning models and automate tuning of hyperparameters."--Resource description page | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Electronic data processing. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a Electronic data processing. |2 fast |0 (OCoLC)fst00906956 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 700 | 1 | |a Tok, Wee-Hyong, |e on-screen presenter. | |
| 711 | 2 | |a O'Reilly Artificial Intelligence Conference |d (2019 : |c New York, N.Y.) |j issuing body. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/videos/~/0636920339601/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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