pyprobml VS PRML

Compare pyprobml vs PRML and see what are their differences.

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pyprobml PRML
3 1
6,257 11,250
1.7% -
6.2 0.0
4 months ago almost 2 years ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

pyprobml

Posts with mentions or reviews of pyprobml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-09.

PRML

Posts with mentions or reviews of PRML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2020-12-31.
  • Probabilistic Machine Learning, Kevin Murphy (2nd edition, 2021)
    3 projects | news.ycombinator.com | 31 Dec 2020
    It's a regression as far as code readability goes for fairly straightforward reasons: almost everything in Matlab is a matrix. Matrices are not first class citizens in Python, and it matters. I use Python a hell of a lot more than Matlab, but for examining how an algorithm works, Matlab wins. Go look at these PRML collections in Python and Matlab and see if you disagree:

    https://github.com/ctgk/PRML

    https://github.com/PRML/PRMLT

What are some alternatives?

When comparing pyprobml and PRML you can also consider the following projects:

numpyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

retrolab - JupyterLab distribution with a retro look and feel 🌅

prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

iterative-grabcut - This algorithm uses a rectangle made by the user to identify the foreground item. Then, the user can edit to add or remove objects to the foreground. Then, it removes the background and makes it transparent.

jaxopt - Hardware accelerated, batchable and differentiable optimizers in JAX.

simfin-tutorials - Tutorials for SimFin - Simple financial data for Python

machine-learning-experiments - 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

football-crunching - Analysis and datasets about football (soccer)

lucid - A collection of infrastructure and tools for research in neural network interpretability.

lightwood - Lightwood is Legos for Machine Learning.

feature-engineering-tutorials - Data Science Feature Engineering and Selection Tutorials