r/datascience · 2023

Most-mentioned books in r/datascience during 2023

This page ranks books by exact tracked mentions in r/datascience within the published source unit for 2023. Counts come from the reconciled subreddit-by-month matrix; a source unit may be a bounded sample.

Books ranked

Tracked mentions in 2023

Sort by upvotes = sum of comment scores on recognized mentions

Clean Code

Robert C. Martin

Robert Martin's case that unreadable functions are a discipline failure, not an inevitability, argued one renamed variable and one extracted method at a time.

5 in 2023

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Aurélien Géron

Aurélien Géron's scikit-learn-to-TensorFlow book that data scientists recommend and interviewers weaponize in the same threads.

4 in 2023

Designing Data-Intensive Applications

Martin Kleppmann

Martin Kleppmann walks backend engineers through every database, queue, and consistency tradeoff they'll eventually get paged about.

3 in 2023

Trustworthy Online Controlled Experiments

Ron Kohavi

A data scientist keeps one book on A/B testing on their desk for a job they don't have yet.

3 in 2023

A Philosophy of Software Design

John Ousterhout

A Stanford professor who invented Tcl spends two hundred pages arguing that hiding complexity behind well-designed modules beats writing more, smaller methods.

2 in 2023

Fluent Python

Luciano Ramalho

A Python developer past the syntax stage opens Fluent Python to learn why dunder methods, iterators, and decorators work the way they do.

2 in 2023

Clean Architecture

Robert C. Martin

Robert Martin's rule: business logic sits at the center of the system, frameworks and databases plug in at the edges, never the other way around.

1 in 2023

Cracking the Coding Interview

Gayle Laakmann McDowell

The book credited with inventing the modern coding interview, argued about like it's also on trial for it.

1 in 2023

Design Patterns

Erich Gamma

Four authors catalog twenty-three recurring object-oriented problems in 1994 and hand every future code review the same argument to have.

1 in 2023

#10

Pattern Recognition and Machine Learning

Christopher M. Bishop

Chris Bishop opens with Bayes' theorem and doesn't let go until three hundred pages of matrices later you understand why a neural network is really just curve-fitting with priors.

1 in 2023

#11

Software Engineering at Google

Titus Winters

Google engineers document how a 25,000-person org ships software that has to last decades — the distinction between 'programmer' and 'engineer' is the whole argument.

1 in 2023