| 000 | 03268cam a2200277zu 4500 | ||
|---|---|---|---|
| 001 | 88856877 | ||
| 003 | FRCYB88856877 | ||
| 005 | 20250107230351.0 | ||
| 006 | m o d | ||
| 007 | cr un | ||
| 008 | 250108s2018 fr | o|||||0|0|||eng d | ||
| 020 | _a9781788839440 | ||
| 035 | _aFRCYB88856877 | ||
| 040 |
_aFR-PaCSA _ben _c _erda |
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| 100 | 1 | _aToomey, Dan | |
| 245 | 0 | 1 |
_aJupyter Cookbook _c['Toomey, Dan'] |
| 264 | 1 |
_bPackt Publishing _c2018 |
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| 300 | _a p. | ||
| 336 |
_btxt _2rdacontent |
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| 337 |
_bc _2rdamdedia |
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| 338 |
_bc _2rdacarrier |
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| 650 | 0 | _a | |
| 700 | 0 | _aToomey, Dan | |
| 856 | 4 | 0 |
_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88856877 _qtext/html _a |
| 520 | _aLeverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassleAbout This BookCreate and share interactive documents with live code, text and visualizationsIntegrate popular programming languages such as Python, R, Julia, Scala with JupyterDevelop your widgets and interactive dashboards with these innovative recipesWho This Book Is ForThis cookbook is for data science professionals, developers, technical data analysts, and programmers who want to execute technical coding, visualize output, and do scientific computing in one tool. Prior understanding of data science concepts will be helpful, but not mandatory, to use this book.What You Will LearnInstall Jupyter and configure engines for Python, R, Scala and moreAccess and retrieve data on Jupyter NotebooksCreate interactive visualizations and dashboards for different scenariosConvert and share your dynamic codes using HTML, JavaScript, Docker, and moreCreate custom user data interactions using various Jupyter widgetsManage user authentication and file permissionsInteract with Big Data to perform numerical computing and statistical modelingGet familiar with Jupyter's next-gen user interface - JupyterLabIn DetailJupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications.The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web.By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it.Style and approachThe recipes in this book are highly practical and very easy to follow, and include tips and tricks that will help you crack any problem that you might come across while getting the most out of your Jupyter notebook. | ||
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