Ciencia de datos: Consejos y trucos para aprender teorías de ciencia de datos de manera efectiva

Name: Ciencia de datos: Consejos y trucos para aprender teorías de ciencia de datos de manera efectiva
Brand: Joiningthedotstv Limited
SKU: 9781913597399
Price: 1440.0 INR
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by William Vance

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ISBN13: 9781913597399
Binding: Paperback
Subject: N/A
Publisher: Joiningthedotstv Limited
Publisher Imprint: Joiningthedotstv Limited
Publication Date: June 26, 2020
Pages: 238
Original Price: USD 19.99
Language: Spanish
Edition: N/A
Item Weight: 323 grams
BISAC Subject(s): Computer Science, Optical Data Processing, and Data Science / General

About The Book

Un cientÃfico de datos es alguien que sabe mÃ¡s de informÃ¡tica que un estadÃstico, y conoce mÃ¡s estadÃsticas que un cientÃfico de la computaciÃ³n. Si bien, en gran medida, esto es cierto, convertirse en un buen cientÃfico de datos requiere el dominio no solo de estas dos Ã¡reas clave, sino tambiÃ©n de algunas teorÃas y modelos cruciales para este campo. Sin embargo, esta Ã¡rea ha demostrado ser muy difÃcil de entender. Los cientÃficos de datos se cansan fÃ¡cilmente de las diversas teorÃas y modelos que deben dominar para sobresalir en el campo.

La creciente tasa de ciencia de datos hoy en dÃa lo ha convertido en un Ã¡rea de referencia para los estudios de computaciÃ³n. Se necesitan cientÃficos de datos en prÃ¡cticamente todos los campos y carreras. Los cientÃficos de datos hacen efectivas plataformas como Facebook, Twitter e incluso sitios mÃ¡s profesionales como LinkedIn. El servicio de un cientÃfico de datos es necesario en profesiones como organizaciones empresariales y financieras, bancos, centros de atenciÃ³n mÃ©dica e incluso bufetes de abogados.

Este libro proporciona una explicaciÃ³n detallada de las teorÃas, algoritmos, estadÃsticas y anÃ¡lisis aplicables al dominio de la ciencia de datos. Da una guÃa paso a paso sobre cÃ³mo se implementan las diversas teorÃas en ciencia de datos. Explica en detalle la diferencia entre los dos tipos principales de regresiones que tenemos: regresiones lineales y no lineales. La explicaciÃ³n sobre Ã¡reas interesantes como la programaciÃ³n R, la subasta, la extracciÃ³n y el anÃ¡lisis de datos, los algoritmos y muchos mÃ¡s estÃ¡n cubiertos en detalle.

La ciencia de datos implica el dominio de las estadÃsticas aplicables al campo. En este libro, se proporcionan fÃ³rmulas para examinar Ã¡reas clave, como el manejo de datos, el anÃ¡lisis de datos y la implementaciÃ³n de datos.

El libro se recomienda a todos los lectores interesados que aspiran a destacarse en el campo de la ciencia de datos.

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