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Linear regression. Part 2, Introduction to real-world machine learning /
"Linear regression is one of the most important machine learning tools. It is the simplest of the predictive modeling techniques and it is widely used, whether on its own or in combination with other techniques. This course teaches the principles and practices of linear regression. It reviews t...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
O'Reilly,
[2017]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Staglianò, Alessandra, |e speaker. | |
| 245 | 1 | 0 | |a Linear regression. |n Part 2, |p Introduction to real-world machine learning / |c with Alessandra Staglianò, Angie Ma, and Gary Willis. |
| 246 | 3 | 0 | |a Introduction to real-world machine learning |
| 264 | 1 | |a [Place of publication not identified] : |b O'Reilly, |c [2017] | |
| 300 | |a 1 online resource (1 streaming video file (1 hr., 1 min., 19 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 | ||
| 511 | 0 | |a Presenter, Alessandra Staglianò, Angie Ma, and Gary Willis. | |
| 500 | |a Title from title screen (viewed September 21, 2017). | ||
| 500 | |a Date of publication taken from resource description page. | ||
| 500 | |a "Part 2 of 6." | ||
| 520 | |a "Linear regression is one of the most important machine learning tools. It is the simplest of the predictive modeling techniques and it is widely used, whether on its own or in combination with other techniques. This course teaches the principles and practices of linear regression. It reviews the meaning of modeling, explains linear regression's key concepts (e.g., cost function, R-squared metric, etc.), describes the practice and need for hypothesis testing, illustrates how to implement linear regression computationally, and showcases an implementation of ridge regression. An understanding of basic mathematics is required, and some knowledge of linear algebra and differential calculus will allow the viewer to understand all of the subtle details."--Resource description page | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Regression analysis. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 6 | |a Analyse de régression. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Artificial intelligence. |2 fast |0 (OCoLC)fst00817247 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 7 | |a Regression analysis. |2 fast |0 (OCoLC)fst01432090 | |
| 700 | 1 | |a Ma, Angie, |e speaker. | |
| 700 | 1 | |a Willis, Gary, |e speaker. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/videos/~/9781492023890/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||