Items related to Software Engineering for Data Scientists: From Notebooks...
Synopsis
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. 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
"synopsis" may belong to another edition of this title.
About the Author
Catherine Nelson is a freelance data scientist and writer. She is currently working on the forthcoming O'Reilly book "Software Engineering for Data Scientists". Previously, she was a Principal Data Scientist at SAP Concur, where she delivered production machine learning applications and developed innovative new features using NLP. She is also co-author of the O'Reilly publication "Building Machine Learning Pipelines", and she is an organizer for Seattle PyLadies, supporting women who code in Python. In her previous career as a geophysicist she studied ancient volcanoes and explored for oil in Greenland. Catherine has a PhD in geophysics from Durham University and a Masters of Earth Sciences from Oxford University.
"About this title" may belong to another edition of this title.
Search results for Software Engineering for Data Scientists: From Notebooks...
Stock Image
Software Engineering for Data Scientists: From Notebooks to Scalable Systems
Published by
O'Reilly Media (edition 1), 2024
ISBN 10: 1098136209
ISBN 13: 9781098136208
Used
Paperback
Seller: BooksRun, Philadelphia, PA, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported. Seller Inventory # 1098136209-8-1
Quantity: 3 available
Stock Image
Software Engineering for Data
Published by
Oreilly & Associates Inc, 2024
ISBN 10: 1098136209
ISBN 13: 9781098136208
Used
Softcover
Seller: SecondSale, Montgomery, IL, U.S.A.
Seller rating 4 out of 5 stars
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Seller Inventory # 00088987668
Quantity: 3 available
Seller Image
Software Engineering for Data Scientists : From Notebooks to Scalable Systems
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition. Seller Inventory # 47219068
Quantity: 2 available
Seller Image
Software Engineering for Data Scientists : From Notebooks to Scalable Systems
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 47219068-n
Quantity: 2 available
Seller Image
Software Engineering for Data Scientists: From Notebooks to Scalable Systems (Paperback or Softback)
Published by
O'Reilly Media 5/21/2024, 2024
ISBN 10: 1098136209
ISBN 13: 9781098136208
New
Paperback or Softback
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
Seller rating 5 out of 5 stars
Paperback or Softback. Condition: New. Software Engineering for Data Scientists: From Notebooks to Scalable Systems 0.92. Book. Seller Inventory # BBS-9781098136208
Quantity: 5 available
Stock Image
Software Engineering for Data Scientists: From Notebooks to Scalable Systems
Published by
Oreilly & Associates Inc, 2024
ISBN 10: 1098136209
ISBN 13: 9781098136208
New
Softcover
Seller: Lakeside Books, Benton Harbor, MI, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books! Seller Inventory # OTF-S-9781098136208
Quantity: Over 20 available
Stock Image
Software Engineering for Data Scientists: From Notebooks to Scalable Systems
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9781098136208
Quantity: Over 20 available
Stock Image
Software Engineering for Data Scientists
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # GB-9781098136208
Quantity: 4 available
Stock Image
Software Engineering for Data Scientists (Paperback)
Published by
O'Reilly Media, Sebastopol, 2024
ISBN 10: 1098136209
ISBN 13: 9781098136208
New
Paperback
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. 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. 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 This practical book bridges the gap between data science and software engineering, clearly explaining how to apply the best practices from software engineering to data science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781098136208
Quantity: 1 available
Seller Image
Software Engineering for Data Scientists
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: New. 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, clearly explaining 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. If you want to write better data science code, this guide covers the essential topics you need (and that are often missing from introductory data science or coding classes), including how to:Understand data structures and object-oriented programmingClearly and skillfully document your codePackage and share your codeIntegrate data science code with a larger codebaseWrite APIsCreate secure codeApply best practices to common tasks such as testing, error handling, and loggingWork more effectively with software engineersWrite more efficient, maintainable, and robust code in PythonPut your data science projects into productionAnd more. Seller Inventory # LU-9781098136208
Quantity: Over 20 available