Found 7 comments on HN
A lot of people in this thread are focusing on technical tools, which is normal for a discussion of this type, but I think that focus is misplaced. Most technical tools are easily learnable and are not the limiting factor is creating good data science products.

(Disclaimer: I wrote the post at the above link).

If you have a sound design you can still create a huge amount of value even with a very simple technical toolset. By the same token, you can have the biggest, baddest toolset in the world and still end up with a failed implementation if you have bad design.

There are resources out there for learning good design. This is a great introduction and points to many other good materials:

W0lf · 2017-06-05 · Original thread
I've gathered all the book titles in this thread and created Amazon affiliate links (if you don't mind. Otherwise you still have all the titles together :-) )

A Pattern Language, Alexander and Ishikawa and Silverstein

Advanced Programming in the Unix Environment , Stevens

Algorithmics: the Spirit of Computing, Harel

Applied Crytography, Wiley

Clean Code, Martin

Clean Coder, Martin

Code Complete, McConnel

Code: The Hidden Language of Computer Hardware and Software, Petzold

Coders at Work, Seibel

Compilers: Principles, Techniques, & Tools, Aho

Computer Systems: A Programmer's Perspective, O'Hallaron and Bryant

Data Flow Analysis: Theory and Practice, Khedker

Dependency Injection in .NET, Seemann

Domain Driven Design, Evans

Fundamentals of Wireless Communication, Tse and Viswanath

Genetic Programming: An Intrduction, Banzhaf

Head First Design Patterns, O'Reilly

Implementing Domain-Driven Design, Vernon

Intrduction to Algorithms, CLRS

Introduction to General Systems Thinking, Weinberg

Joy of Clojure, Fogus and Houser

Let over Lambda, Hoyte

Operating Systems: Design and Implementation, Tanenbaum

Parsing Techniques, Grune and Jacobs

Peopleware: Productive Projects and Teams, DeMarco and Lister

Programming Pearls, Bentley

Software Process Design: Out of the Tar Pit, McGraw-Hill

Software Runaways, Glass

Sorting and Searching, Knuth

Structure and Interpretation of Computer Programs, Abelson and Sussman

The Art of Unit Testing, Manning

The Art of Unix Programming, ESR

The Design of Design: Essays from a Computer Scientist, Brooks

The Effective Engineer, Lau

The Elements of Style, Strunk and White

The Healthy Programmer, Kutner

The Linux Programming Interface, Kerrisk

The Mythical Man-Month, Brooks

The Practice of Programming, Kernighan and Pike

The Pragmatic Programmer, Hunt and Thomas

The Psychology of Computer Programming, Weinberg

Transaction Processing: Concepts and Techniques, Gray and Reuter

Types and Programming Languages, Pierce

Understanding MySQL Internals, Pachev

Working Effectively with Legacy Code, Feathers

Zen of graphics programming, Abrash

Thanks for the link. Let me repay you with one:

cedotal · 2016-02-11 · Original thread
Yes -- It's Fred Brooks' own "The Design of Design:"
csours · 2015-03-16 · Original thread
Putting aside all the ad-hominem and everything-is-terrible, I think I learned a lot from following the references Tef makes in this talk.

Some references (sorry for the formatting, if this becomes a thing I'll do the wiki and the logo):


Blub Paradox:

Perl and 9/11:


Waterfall (same pdf, linking from 2 sources):

Conway's law:

Unrelated, Pournelle's Iron Law of Bureaucracy (I just like this law):

X-Y Problem:

Atwood, Don't Learn to Code:

Wason selection task:


Amazon Links, no referral:

bad_user · 2011-11-25 · Original thread

Somebody also suggested "The Design of Design: Essays from a Computer Scientist", by Frederick P. Brooks (Mythical Man Month) ...

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