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Hands-on data science with Anaconda : utilize the right mix of tools to create high-performance data science applications /
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 020 | |a 9781788831192 | ||
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| 049 | |a UAMI | ||
| 100 | 1 | |a Yan, Yuxing, |e author. | |
| 245 | 1 | 0 | |a Hands-on data science with Anaconda : |b utilize the right mix of tools to create high-performance data science applications / |c Dr. Yuxing Yan, James Yan. |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2018. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 588 | 0 | |a Online resource; title from title page (Safari, viewed June 27, 2018). | |
| 520 | 8 | |a Annotation |b Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, AnacondaKey Features-Use Anaconda to find solutions for clustering, classification, and linear regression-Analyze your data efficiently with the most powerful data science stack-Use the Anaconda cloud to store, share, and discover projects and librariesBook DescriptionAnaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You'll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You'll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you're accustomed to all this, you'll start with operations in data science such as cleaning, sorting, and data classification. You'll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you'll learn how to visualize data using the packages available for Julia, Python, and R. What you will learnPerform cleaning, sorting, classification, clustering, regression, and dataset modeling using AnacondaUse the package manager conda and discover, install, and use functionally efficient and scalable packagesGet comfortable with heterogeneous data exploration using multiple languages within a projectPerform distributed computing and use Anaconda Accelerate to optimize computational powersDiscover and share packages, notebooks, and environments, and use shared project drives on Anaconda CloudTackle advanced data prediction problemsWho this book is forHands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It's also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected. | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 630 | 0 | 0 | |a ANACONDA (Electronic resource) |
| 630 | 0 | 7 | |a ANACONDA (Electronic resource) |2 fast |0 (OCoLC)fst01726986 |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Information visualization. | |
| 650 | 0 | |a Electronic data processing. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Visualisation de l'information. | |
| 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 | |
| 700 | 1 | |a Yan, James, |e author. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781788831192/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||