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257 titles
Life in Code
Ellen Ullman
Not reviewed yet
Practical Statistics for Data Scientists
Peter Bruce
Not reviewed yet
R for Data Science
Hadley Wickham
Not reviewed yet
Radical Candor
Kim Scott
Not reviewed yet
Serious Cryptography
Jean-Philippe Aumasson
Not reviewed yet
Terraform: Up & Running
Yevgeniy Brikman
Not reviewed yet
Web Performance in Action
Jeremy L. Wagner
Not reviewed yet
Atomic Design
Brad Frost
Not reviewed yet
Chaos Monkeys
Antonio García Martínez
Not reviewed yet
Deep Learning
Ian Goodfellow
Not reviewed yet
Deep Work
Cal Newport
Not reviewed yet
Grokking Algorithms
Aditya Y. Bhargava
Not reviewed yet
Infrastructure as Code
Kief Morris
Not reviewed yet
Never Split the Difference
Chris Voss
Not reviewed yet
Pattern Recognition and Machine Learning
Christopher M. Bishop
Not reviewed yet
Programming Phoenix
Chris McCord
Not reviewed yet
The DevOps Handbook
Gene Kim
Not reviewed yet
Weapons of Math Destruction
Cathy O'Neil
Not reviewed yet
Automate the Boring Stuff with Python
Al Sweigart
Not reviewed yet
Building Microservices
Sam Newman
Not reviewed yet
Clojure for the Brave and True
Daniel Higginbotham
Not reviewed yet
Computer Systems: A Programmer's Perspective
Randal E. Bryant
Not reviewed yet
Data Science from Scratch
Joel Grus
Not reviewed yet
Debugging Teams
Brian W. Fitzpatrick
Not reviewed yet
Often recommended marks titles that appear on a large share of curated engineering reading lists, from apublic meta-analysis of 36 listspublished in 2019. It is not a rating and nobody is quoted. The list predates several now-standard books, so no badge means “not on that list”, never “not worth reading”. Stars come from readers here, and only from readers.
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