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r/MachineLearning · 2021

Most-mentioned books in r/MachineLearning during 2021

This page ranks books by exact tracked mentions in r/MachineLearning within the published source unit for 2021. Counts come from the reconciled subreddit-by-month matrix; a source unit may be a bounded sample.

6
Books ranked
10
Tracked mentions in 2021
Sort by upvotes = sum of comment scores on recognized mentions
Cover of Designing Data-Intensive Applications #1

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 2021
Cover of Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow #2

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.

3 in 2021
Cover of Code Complete #3

Code Complete

Steve McConnell

Steve McConnell's seven-hundred-page argument that construction, not design or testing, is where most software quality is actually won or lost.

1 in 2021
Cover of Cracking the Coding Interview #4

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 2021
Cover of Pattern Recognition and Machine Learning #5

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 2021
Cover of The Mythical Man-Month #6

The Mythical Man-Month

Frederick P. Brooks Jr.

Fred Brooks managed IBM's late-1960s OS/360 project, then wrote the book explaining why adding more programmers only made it later.

1 in 2021