Python for data science
The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s and named after Monty Python that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video gam...
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| Principais autores: | , |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Hoboken, NJ :
John Wiley & Sons
C 2019.
Paris : Cyberlibris 2019. |
| Edição: | 2e édition. |
| coleção: | For dummies
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| Assuntos: | |
| Acesso em linha: | Accès Université d'Orléans et IFPM |
| Nota: |
Description d'après la consultation, 2022-08-25 Titre provenant de l'écran titre Numérisation de l'édition de Hoboken : John Wiley & Sons, C 2019 La pagination de l'édition imprimée correspondante est de XVI-467 pages Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Python for data science, by John Paul Mueller and Luca Massaron, 2e édition, 2019, Hoboken, NJ, John Wiley & Sons, Inc., 1 vol. (xvi, 467 p.), --For dummies, 1-119-54762-8 |
| Resumo: | The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s and named after Monty Python that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction. |
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| Descrição do item: | Description d'après la consultation, 2022-08-25 Titre provenant de l'écran titre Numérisation de l'édition de Hoboken : John Wiley & Sons, C 2019 La pagination de l'édition imprimée correspondante est de XVI-467 pages Cyberlibris (ScholarVox) corpus Informatique |
| Bibliografia: | Index |
| ISBN: | 9781119547648 |
| Acesso: | L'accès à cette ressource est réservé aux usagers des établissements qui en ont fait l'acquisition L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris |