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210123 ||| eng |
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|a Salon, Data
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| 245 |
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|a Machine Learning & AI
|h [electronic resource]
|b Demystified for TV Advertising
|c Salon, Data
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| 250 |
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|a 1st edition
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| 260 |
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|b Data Science Salon
|c 2019
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| 300 |
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|a 1 video file, approximately 26 min.
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| 653 |
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|a Vidéo en continu
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| 653 |
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|a Vidéos sur Internet
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| 653 |
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|a streaming video / aat
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| 653 |
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|a Internet videos / http://id.loc.gov/authorities/subjects/sh2007001612
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| 653 |
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|a Streaming video / http://id.loc.gov/authorities/subjects/sh2005005237
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a Mode of access: World Wide Web
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| 500 |
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|a Made available through: Safari, an O'Reilly Media Company
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|z 00000MLFFM788W7Y
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| 856 |
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|u https://learning.oreilly.com/videos/~/00000MLFFM788W7Y/?ar
|x Verlag
|3 Volltext
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|a E VIDEO
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| 520 |
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|a 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
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