
Software Engineering for Data Scientists
From Notebooks to Scalable Systems
O'Reilly Media · Print & ebook · May 21, 2024
Data science happens in code.
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- Who it’s for
- Learn to apply software engineering practices to data science code, from notebooks to production systems.
- Genres
- Data Science, Software Development, Python Programming
- Published
- O'Reilly Media, May 21, 2024
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Start with this bookAbout this book
Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science. Examples are provided in Python, drawn from popular packages such as NumPy and pandas.
Continue reading
If you want to write better data science code, this guide covers the essential topics that are often missing from introductory data science or coding classes, including how to: - Understand data structures and object-oriented programming - Clearly and skillfully document your code - Package and share your code - Integrate data science code with a larger code base - Learn how to write APIs - Create secure code - Apply best practices to common tasks such as testing, error handling, and logging - Work more effectively with software engineers - Write more efficient, maintainable, and robust code in Python - Put your data science projects into production - And more
Data Science in Python
Learn to apply software engineering practices to data science code, from notebooks to production systems.
Come here for
- Python examples using NumPy and pandas
- Guidance on packaging, APIs, testing, and logging
Expect
- Coverage of data structures and object-oriented programming
- Practical guidance on documentation, security, and code sharing
Where it sits
| Python Programming | 69% |
|---|---|
| Data Science | 56% |
| Software Development | 51% |
Percentages are BookFrontier’s reading of the book.
Publisher categories
- AI & Machine Learning
- Systems Architecture
- Data Mining
- Programming Basics
Show all 6 publisher categories
- Systems Design
- Machine Learning
- Authors
- Catherine Nelson
- Publisher
- O'Reilly Media
- Published
- May 21, 2024
- Format
- Print & ebook
- Reading lane
- AI & Machine Learning