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Machine Learning & AI Demystified for TV Advertising /

Presented by Diane Yu, CTO and Cofounder at FreeWheel, Comcast As the leading provider of financial and company data, Bloomberg has access to vast amounts of data on a daily basis. There are two common challenges when working directly with raw data. One is the need to discover and extract data repre...

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Detalles Bibliográficos
Autor principal: Salon, Data (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico Video
Idioma:Inglés
Publicado: Data Science Salon, 2019.
Edición:1st edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:Presented by Diane Yu, CTO and Cofounder at FreeWheel, Comcast As the leading provider of financial and company data, Bloomberg has access to vast amounts of data on a daily basis. There are two common challenges when working directly with raw data. One is the need to discover and extract data represented in the natural document format that is not machine-readable. Another requirement is validating and ensuring that the data is of high-quality since it is required for building models for predictions, classifications, and various analytics tasks. This talk will cover ways in which data science and machine learning can be used to address these two challenges: (1) ingesting your data by extracting what is contained in natural document format and (2) cleaning your ingested data.
Descripción Física:1 online resource (1 video file, approximately 26 min.)