Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
By: James Densmore
3.74
Format: 274 pages, Paperback
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse …
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1. Graph Databases
By: Ian Robinson , Jim Webber , Emil Eifrem
4.04
Format: 192 pages, Paperback
Discover how graph databases can help you manage and query highly connected data. With this practic… read more
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- technical
- nonfiction
- programming
- software
- technology
2. The Pragmatic Programmer: From Journeyman to Master
By: Dave Thomas , Andy Hunt
3.28
Format: 404 pages, Paperback
-- Ward Cunningham Straight from the programming trenches, The Pragmatic Programmer cuts through th… read more
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Similar categories in None's Designing Data-Intensive Applications book and James Densmore's Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
4. The Phoenix Project: A Novel About IT, DevOps, and Helping Your Business Win
By: Gene Kim , George Spafford , Kevin Behr
4.16
Format: 200 pages, Hardcover
Bill is an IT manager at Parts Unlimited. It's Tuesday morning and on his drive into the office, Bi… read more
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5. The Manager's Path: A Guide for Tech Leaders Navigating Growth and Change
By: Camille Fournier
3.75
Format: 288 pages, Paperback
Managing people is difficult wherever you work, but the tech industry as a whole is pretty bad at i… read more
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6. Fundamentals of Software Architecture: An Engineering Approach
By: Mark Richards
4.26
Format: 419 pages, Paperback
Although salary surveys worldwide regularly identify software architect as one of the top ten best … read more
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- technical
- nonfiction
- programming
- software
- technology
7. Fundamentals of Data Engineering: Plan and Build Robust Data Systems
By: Joe Reis
4.25
Format: 426 pages, Paperback
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scient… read more
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- technical
- nonfiction
- programming
- software
- technology
8. Tidy First?: A Personal Exercise in Empirical Software Design
By: Kent Beck
3.95
Format: 122 pages, Paperback
Messy code is a nuisance. "Tidying" code, to make it more readable, requires breaking it up into ma… read more
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- technical
- nonfiction
- programming
- software
- technology
9. Spark: The Definitive Guide: Big Data Processing Made Simple
By: Bill Chambers
4.15
Format: 951 pages, Kindle Edition
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the c… read more
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- technical
- nonfiction
- programming
- reference
- technology
10. Data Mesh: Delivering Data-Driven Value at Scale
By: Zhamak Dehghani
3.84
Format: 384 pages, Paperback
We're at an inflection point in data, where our data management solutions no longer match the compl… read more
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- technical
- nonfiction
- programming
- software
- technology
11. Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
By: Valliappa Lakshmanan
4.16
Format: 400 pages, Paperback
The design patterns in this book capture best practices and solutions to recurring problems in mach… read more
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- technical
- nonfiction
- programming
- software
- technology
12. Observability Engineering: Achieving Production Excellence
By: Charity Majors
3.77
Format: 318 pages, Paperback
Observability is critical for engineering, managing, and improving complex business-critical system… read more
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- technical
- nonfiction
- programming
- software
- technology
13. Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
By: James Densmore
3.74
Format: 274 pages, Paperback
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse … read more
Want to Read $ 11.99Similar categories in James Densmore's Data Pipelines Pocket Reference: Moving and Processing Data for Analytics book and James Densmore's Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
- technical
- nonfiction
- programming
- software
- reference
- technology
14. Data Quality Fundamentals
By: Barr Moses
3.76
Format: 288 pages, Unknown Binding
Do your product dashboards look funky? Are your quarterly reports stale? Is the dataset you're usin… read more
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- programming
- nonfiction
- technology
15. Building Event-Driven Microservices: Leveraging Organizational Data at Scale
By: Adam Bellemare
3.69
Format: 321 pages, Paperback
Organizations today often struggle to balance business requirements with ever-increasing volumes of… read more
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- technical
- nonfiction
- programming
- software
- technology
16. Deep Learning with PyTorch
By: Eli Stevens
4.18
Format: 450 pages, Paperback
Every other day we hear about new ways to put deep learning to good use: improved medical imaging, … read more
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- technical
- nonfiction
- programming
- software
- technology
17. Interpretable Machine Learning: A Guide For Making Black Box Models Explainable
By: Christoph Molnar
4.71
Format: 540 pages, Kindle Edition
Interpretable Machine Learning is a comprehensive guide to making machine learning models interpret… read more
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- programming
18. Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data
By: Ankur A Patel
3.71
Format: 359 pages, Paperback
Many industry experts consider unsupervised learning the next frontier in artificial intelligence, … read more
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- technology
- reference
- programming
19. Feature Engineering for Machine Learning
By: Alice Zheng
3.86
Format: 218 pages, Paperback
Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely ex… read more
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- programming
- technology
- nonfiction
- technical
20. Financial Theory with Python
By: Yves Hilpisch
3.50
Format: 201 pages, Paperback
Nowadays, finance, mathematics, and programming are intrinsically linked. Financial Theory with Pyt… read more
Want to Read $ 31.34Similar categories in Yves Hilpisch's Financial Theory with Python book and James Densmore's Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
- technology
21. Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python
By: Deepak K. Kanungo
3.71
Format: 264 pages, Paperback
There are several reasons why probabilistic machine learning represents the next-generation ML fram… read more
Want to Read $ 48.99Similar categories in Deepak K. Kanungo's Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python book and James Densmore's Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
