PRML
pyprobml
| PRML | pyprobml | |
|---|---|---|
| 1 | 3 | |
| 11,250 | 6,257 | |
| - | 0.8% | |
| 0.0 | 6.2 | |
| almost 2 years ago | 5 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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PRML
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Probabilistic Machine Learning, Kevin Murphy (2nd edition, 2021)
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
pyprobml
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Best Possible Book Recommended for Machine Learning [Discussion] [D] [Recommendation]
Another great book is Kevin Murphy’s Machine Learning: A probabilistic approach. He just launched the second version of his book and he has a Python repo for the models and graphs: https://github.com/probml/pyprobml
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Probabilistic Machine Learning, Kevin Murphy (2nd edition, 2021)
This exists actually, it's not complete yet (I think?) but it covers a lot of the material in the book:
https://github.com/probml/pyprobml
What are some alternatives?
retrolab - JupyterLab distribution with a retro look and feel 🌅
numpyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
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.
prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop
simfin-tutorials - Tutorials for SimFin - Simple financial data for Python
jaxopt - Hardware accelerated, batchable and differentiable optimizers in JAX.
football-crunching - Analysis and datasets about football (soccer)
machine-learning-experiments - 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
lucid - A collection of infrastructure and tools for research in neural network interpretability.
feature-engineering-tutorials - Data Science Feature Engineering and Selection Tutorials
lightwood - Lightwood is Legos for Machine Learning.