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Learning Jupyter 5: Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab, 2nd Edition 2nd ed. Edition
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Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples.
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What Stands Out
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- Learn how to use Jupyter 5.x features such as cell tagging and attractive table styles
- Leverage big data tools and datasets with different Python packages
- Integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia
- Master interactive widgets and namespaces and work with Jupyter in a multi-user mode
- Install and run the Jupyter Notebook system on your machine
- Access big data in Jupyter for dealing with large datasets using Spark
| Publisher | Packt Publishing |
| Publication date | August 30, 2018 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 282 pages |
| ISBN-10 | 1789137403 |
| ISBN-13 | 978-1789137408 |
| Item Weight | 1.08 pounds (490 grams) |
| Dimensions | 7.5 x 0.64 x 9.25 inches (19.1 x 1.6 x 23.5 cm) |
Who Should Buy?
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Data Scientists
Ideal for data scientists looking to enhance data analysis and visualization skills using interactive notebooks.
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Educators
Useful for educators teaching programming or data science, providing interactive coding examples for students.
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Developers
Beneficial for developers needing a versatile platform to test and prototype code across multiple programming languages.
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Beginner Programmers
Novice programmers may find the concepts overwhelming without foundational programming knowledge or experience.
Product Description
Learning Jupyter 5: Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab, 2nd Edition 2nd ed. Edition
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Pros
- Comprehensive coverage
- User-friendly approach
- Practical examples
- Interactive learning
- Up-to-date content
Cons
- Occasional inaccuracies
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Features & Benefits
- Learn to use Jupyter Notebook to create and share documents containing live code, equations, visualizations and explanatory text
- Explore the integration of Jupyter with different programming languages such as R, Python, Java, JavaScript, and Julia
- Master interactive widgets and namespaces and work with Jupyter in a multi-user mode
- Access big data in Jupyter for dealing with large datasets using Spark
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