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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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Staglianò, Alessandra (Orador), Ma, Angie (Orador), Willis, Gary (Orador)
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly, [2017]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:"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
Notas:Title from title screen (viewed September 21, 2017).
Date of publication taken from resource description page.
"Part 2 of 6."
Descripción Física:1 online resource (1 streaming video file (1 hr., 1 min., 19 sec.))