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r/MachineLearning · 2020

Most-mentioned books in r/MachineLearning during 2020

This page ranks books by exact tracked mentions in r/MachineLearning within the published source unit for 2020. Counts come from the reconciled subreddit-by-month matrix; a source unit may be a bounded sample.

6
Books ranked
9
Tracked mentions in 2020
Sort by upvotes = sum of comment scores on recognized mentions
Cover of Pattern Recognition and Machine Learning #1

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.

3 in 2020
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.

2 in 2020
Cover of Clean Code #3

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.

1 in 2020
Cover of Design Patterns #4

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 2020
Cover of Effective Python #5

Effective Python

Brett Slatkin

Brett Slatkin's Python style guide gets read cover to cover, while its usual shelf-mate Fluent Python becomes something to scare junior devs with instead.

1 in 2020
Cover of Fluent Python #6

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.

1 in 2020