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Beginning data science with Python and Jupyter /
"Getting started with data science doesn't have to be an uphill battle. This step-by-step video course is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on P...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Packt Publishing,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 049 | |a UAMI | ||
| 100 | 1 | |a Villa, Chris Dalla, |e speaker. | |
| 245 | 1 | 0 | |a Beginning data science with Python and Jupyter / |c Chris Dalla Villa. |
| 264 | 1 | |a [Place of publication not identified] : |b Packt Publishing, |c 2018. | |
| 300 | |a 1 online resource (1 streaming video file (2 hr., 49 min., 1 sec.)) | ||
| 336 | |a two-dimensional moving image |b tdi |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 337 | |a video |b v |2 rdamedia | ||
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| 511 | 0 | |a Presenter, Chris Dalla Villa. | |
| 500 | |a Title from resource description page (Safari, viewed November 26, 2018). | ||
| 520 | |a "Getting started with data science doesn't have to be an uphill battle. This step-by-step video course is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll start with understanding the basics of Jupyter and its standard features. You'll be analyzing an example of a data analytics report. After analyzing a data analytics report, next step is to implement multiple classification algorithms. We'll then show you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context. Finish up by learning to visualize these data interactively."--Resource description page | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Information visualization. | |
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Electronic data processing. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Visualisation de l'information. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 7 | |a Electronic data processing. |2 fast |0 (OCoLC)fst00906956 | |
| 650 | 7 | |a Information visualization. |2 fast |0 (OCoLC)fst00973185 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 7 | |a Python (Computer program language) |2 fast |0 (OCoLC)fst01084736 | |
| 655 | 4 | |a Electronic videos. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/videos/~/9781789532449/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||