Learning Jupyter 5: Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab
bCreate and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter/b h4Key Features/h4 ulliLearn how to use Jupyter 5.x features such as cell tagging and attractive table styles /li liLeverage big data tools and datasets with differe...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2018
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| Ausgabe: | 2 |
| Schlagworte: | |
| Zusammenfassung: | bCreate and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter/b h4Key Features/h4 ulliLearn how to use Jupyter 5.x features such as cell tagging and attractive table styles /li liLeverage big data tools and datasets with different Python packages /li liExplore multiple-user Jupyter Notebook servers /li /ul h4Book Description/h4 The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you've explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. h4What you will learn/h4 ulliInstall and run the Jupyter Notebook system on your machine /li liImplement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook /li liUse interactive widgets to manipulate and visualize data in real time /li liStart sharing your Notebook with colleagues /li liInvite your colleagues to work with you on the same Notebook /li liOrganize your Notebook using Jupyter namespaces /li liAccess big data in Jupyter for dealing with large datasets using Spark /li /ul h4Who this book is for/h4 Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively |
| Beschreibung: | 1 Online-Ressource (282 Seiten) |
| ISBN: | 9781789137446 |
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| 520 | |a bCreate and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter/b h4Key Features/h4 ulliLearn how to use Jupyter 5.x features such as cell tagging and attractive table styles /li liLeverage big data tools and datasets with different Python packages /li liExplore multiple-user Jupyter Notebook servers /li /ul h4Book Description/h4 The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. | ||
| 520 | |a Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you've explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. | ||
| 520 | |a h4What you will learn/h4 ulliInstall and run the Jupyter Notebook system on your machine /li liImplement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook /li liUse interactive widgets to manipulate and visualize data in real time /li liStart sharing your Notebook with colleagues /li liInvite your colleagues to work with you on the same Notebook /li liOrganize your Notebook using Jupyter namespaces /li liAccess big data in Jupyter for dealing with large datasets using Spark /li /ul h4Who this book is for/h4 Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively | ||
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| spelling | Toomey, Dan Verfasser aut Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab Toomey, Dan 2 Birmingham Packt Publishing Limited 2018 1 Online-Ressource (282 Seiten) txt rdacontent c rdamedia cr rdacarrier bCreate and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter/b h4Key Features/h4 ulliLearn how to use Jupyter 5.x features such as cell tagging and attractive table styles /li liLeverage big data tools and datasets with different Python packages /li liExplore multiple-user Jupyter Notebook servers /li /ul h4Book Description/h4 The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you've explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. h4What you will learn/h4 ulliInstall and run the Jupyter Notebook system on your machine /li liImplement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook /li liUse interactive widgets to manipulate and visualize data in real time /li liStart sharing your Notebook with colleagues /li liInvite your colleagues to work with you on the same Notebook /li liOrganize your Notebook using Jupyter namespaces /li liAccess big data in Jupyter for dealing with large datasets using Spark /li /ul h4Who this book is for/h4 Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively COMPUTERS / Data Visualization COMPUTERS / Data Modeling & Design |
| spellingShingle | Toomey, Dan Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab COMPUTERS / Data Visualization COMPUTERS / Data Modeling & Design |
| title | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab |
| title_auth | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab |
| title_exact_search | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab |
| title_exact_search_txtP | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab |
| title_full | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab Toomey, Dan |
| title_fullStr | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab Toomey, Dan |
| title_full_unstemmed | Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab Toomey, Dan |
| title_short | Learning Jupyter 5 |
| title_sort | learning jupyter 5 explore interactive computing using python java javascript r julia and jupyterlab |
| title_sub | Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab |
| topic | COMPUTERS / Data Visualization COMPUTERS / Data Modeling & Design |
| topic_facet | COMPUTERS / Data Visualization COMPUTERS / Data Modeling & Design |
| work_keys_str_mv | AT toomeydan learningjupyter5exploreinteractivecomputingusingpythonjavajavascriptrjuliaandjupyterlab |