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Abelson & Sussman — Structure and Interpretation of Computer Programs
Fundamental of computer programming. The entry-level CS subject at MIT.
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Aditya Bhargava — Grokking Algorithms
A friendly version of CLRS
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Andrew S. Tanenbaum — Computer Networks
Classic introduction into computer networks
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Cal Newport — Deep Work
Prefer deep-thinking over shallowness. Switching tasks reduce effeciency
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Cielen, Meysman & Ali — Introducing Data Science
Data science fundamentals
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Cormen, Leiserson, Rivest, Stein — Introduction to Algorithms
Uniquely combines rigor and comprehensiveness. The leading algorithms text in universities worldwide and the standard reference for professionals. Technical background is mandatory here
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David Beazley & Brian K. Jones — Python Cookbook
Practical recipes written and tested with Python 3.3, for Python developers. From my perspective, David Beazley produces information in the most effecient way
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David C. Krakauer — An Introduction to the Foundations of Complexity Science
An SFI tries to shape complexity into its own discipline. How simple parts give rise to emergent, adaptive, information-processing systems, with information a co-equal pillar beside matter and energy
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David Thomas & Andrew Hunt — The Pragmatic Programmer
The handbook with recommendations for utilitarian (pragmatic) approach in software development
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Eric Evans — Domain-Driven Design (2003)
Building Complex System with a "Domain" (field) oriented approach. Domain Driven Design defines mechanics for nested design patterns, like Repository, CQRS, etc. One of the best Design Patterns in my opinion
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Eric Evans — Getting Started with DDD When Surrounded by Legacy Systems
4 strategies for getting started with DDD when you have a big Legacy System
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François Chollet — Deep Learning with Python
Keras creator learning curve proposal. Includes Python deep learning practical techniques