Programmer and essayist, formerly of Amazon, Google and Grab; author of the Stevey's Drunken Blog Rants and Stevey's Blog Rants essays.
loved
I've read a ton of data-structures and algorithms books, and I've never found one like this one. Its unconventional approach is refreshing and keeps you interested.
His 'Ten Great Books' post (Stevey's Drunken Blog Rants), introduced as 'ten books that I really enjoyed, and that I'd recommend to anyone who's a computer programmer', limited to books he has finished and rereads. The page carries no publication date; the only date on it is an inline note dated 12/13/2004, so the post is from 2004 or earlier.
Programmer and writer on computer architecture, performance and software reliability; has worked on hardware and software at Centaur Technology, Google and Microsoft, and writes at danluu.com.
likedaffiliate link
The longer, more comprehensive, more practical, less math-y version of Dasgupta. It's similar in that it attempts to teach you how to identify problems, use the correct algorithm, and give a clear explanation of the algorithm.
'Programming book recommendations and anti-recommendations' — a topic-by-topic list of the technical books he has read, with what each one is and is not good for. The site gives no day, only 10/16 in its index.
Statistician and software developer; chief scientist at RStudio/Posit and creator of the tidyverse of R packages.
recommended
To me, this book is an illustration of the power of names. Today, in the era of Google, if you know the name of something, you can find out about it with a simple search. But if you don't know of what you're looking for, it suddenly becomes much harder to find it. Having in the back of your head the names of common algorithms that help you solve problems is really powerful.
Five Books interview on computer science books for data scientists
Every entry is a verbatim quote and a link to the public post it came from. Nothing is paraphrased. If it is not on record somewhere public, it is not here.
The verdict is what they actually said: loved and liked are explicit; recommended means they told others to get it; uses means they only say they use it; read is a book on their public shelf with no verdict; mixed and disliked are kept too.
A dashed affiliate link, sponsored or their own label means the post disclosed a relationship. It is shown, never hidden.
The shading behind a date shows how dated a recommendation is for its kind of thing.
The shading behind a date shows how dated a recommendation is, for its kind of thing. Fully green is recent. It drains a quarter at a time as the post gets older, and is empty once it reads as dated.
What counts as old depends on the thing. A laptop praised four years ago has been replaced twice; a book loved twenty years ago is probably still loved. The shading is gone after about:
Hardware, services4 years
Software5 years
Podcasts, courses, other8 years
Books25 years
Stripes mean the post carries no date and the date shown is an estimate. No date at all, no shading.