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What is pml-book?

probml/pml-book — explained in plain English

Analysis updated 2026-06-26

★ 5,563Jupyter NotebookAudience · researcherComplexity · 1/5Setup · easy

In one sentence

GitHub home for a three-volume textbook series on machine learning taught through probability and statistics, written by Kevin Murphy.

Mindmap

mindmap
  root((pml-book))
    What it does
      Textbook series
      Three volumes
      Probability approach
    Topics
      Intro ML Book 1
      Advanced ML Book 2
      Classic 2012 Book 0
    Audience
      ML researchers
      Students
    Format
      Jupyter notebooks
      External figures
Click or tap to explore — scroll the page freely

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Read or reference an introductory machine learning textbook grounded in probability theory.

USE CASE 2

Access code notebooks and figures that accompany the Probabilistic Machine Learning book series.

USE CASE 3

Use as a structured study guide for learning machine learning from a statistical perspective.

What is it built with?

Jupyter NotebookPython

How does it compare?

probml/pml-bookdibgerge/ml-coursera-python-assignmentskarpathy/neuraltalk2
Stars5,5635,5665,579
LanguageJupyter NotebookJupyter NotebookJupyter Notebook
Setup difficultyeasyeasyhard
Complexity1/51/54/5
Audienceresearcherresearcherresearcher

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

So what is it?

This repository is the GitHub home for a series of textbooks on machine learning written by Kevin Murphy, a researcher in the field. The series is titled "Probabilistic Machine Learning" and approaches the subject through the lens of probability and statistics rather than treating machine learning as a purely algorithmic or engineering discipline. The repository README is minimal. It lists three books in the series with links to their respective pages: Book 0 is a 2012 volume titled "Machine Learning: A Probabilistic Perspective," Book 1 is a 2022 introduction to probabilistic machine learning, and Book 2 is a 2023 volume covering advanced topics. The actual content, including code notebooks and figures, is hosted externally rather than described in detail here. The README provides no further information about installation, usage, or licensing.

Copy-paste prompts

Prompt 1
I am studying the Probabilistic Machine Learning book by Kevin Murphy. Can you explain the concept of [topic] in plain English using examples from the book?
Prompt 2
Show me a Python/Jupyter example that demonstrates [concept from the pml-book series] step by step.
Prompt 3
What are the key differences between pml-book Volume 1 and Volume 2, and which should I read first if I already know basic statistics?
Prompt 4
Help me work through an exercise from Kevin Murphy's Probabilistic Machine Learning book on [specific topic].

Frequently asked questions

What is pml-book?

GitHub home for a three-volume textbook series on machine learning taught through probability and statistics, written by Kevin Murphy.

What language is pml-book written in?

Mainly Jupyter Notebook. The stack also includes Jupyter Notebook, Python.

How hard is pml-book to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is pml-book for?

Mainly researcher.

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