pyro
nbdime
pyro | nbdime | |
---|---|---|
9 | 7 | |
8,364 | 2,595 | |
0.5% | 0.2% | |
8.4 | 8.7 | |
10 days ago | about 2 months ago | |
Python | TypeScript | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
pyro
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Show HN: Designing Bridges with PyTorch
Mostly I use pytorch for statistical modeling https://pyro.ai . Under the hood that package uses a lot of Monte Carlo integration and variational methods (i.e. integration by optimization). It does support neural nets, but probably >80% of pyro users stick to simpler hierarchical Bayesian models.
- Pyro: The Universal, Probablistic Programming Language
- The Jupyter+Git problem is now solved
- Pyro: Deep universal probabilistic programming with Python and PyTorch
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Computational Bayesian Inference Techniques
Amortized Variational Inference (Like done in pyro.ai with neural networks)
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[P] torchegranate: a PyTorch rewrite of the pomegranate library for probabilistic modeling
Can you compare this to Pyro, which is also built on top of PyTorch?
- [Q] Updated book or review paper on MCMC methods
- Is anyone here working in uncertainty estimation in neural networks?
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[D] Do you train and deploy models using just one framework or multiple frameworks at work?
Using pyod, statmodels, scikit-learn, Tensorflow and pyro.ai (that is using PyTorch as backend). I always use the same framework for training and for production.
nbdime
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Stuff I Learned during Hanukkah of Data 2023
I remember hearing about nbdime and thinking it sounded useful, but I've never really needed it since I rarely use Jupyter in the first place. But then I made some changes to my Hanukkah of Data 2023 notebook to work with the follow-up "speed run" challenge (a new dataset and slightly tweaked clues), and the native Git diff was too noisy to be useful. nbdime came to the rescue! Here are the changes I had to make for days 2 and 3 during the speed run:
- The Jupyter+Git problem is now solved
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Ask HN: Are there any good Diff tools for Jupyter Notebooks?
[5] ReviewNB for reviewing & diff'ing notebook PRs / Commits on GitHub
Disclaimer: While I’m the author of last two (GitPlus & ReviewNB), I’ve represented the overall landscape in an unbiased way. I've been working on this specific problem for 3+ years & regularly talk to teams who use GitHub with notebooks.
[1] https://nbdime.readthedocs.io
- Notebooks suck: change my mind
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What if Git worked with Programming Languages?
Interesting they mentioned Jupyter Notebooks but not NBDime https://github.com/jupyter/nbdime which is a Jupyter plugin specifically to address this problem. Without it, diffing notebooks is not feasible.
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Jupyter diff in Magit
A bit off-topic but someone might know; I'm working with jupyter notebook files (ipynb) which are basically json files. Git diff is very noisy so there's nbdime which works great in the CLI. Is there a way to have Magit aware of its integration with git diff?
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The Notepad++
I use nbdime which allows you to ignore parts of a notebook (e.g. outputs) when diffing.
What are some alternatives?
PyMC - Bayesian Modeling and Probabilistic Programming in Python
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
scikit-learn - scikit-learn: machine learning in Python
poetry-dynamic-versioning - Plugin for Poetry to enable dynamic versioning based on VCS tags
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
nvim-treesitter-context - Show code context
trueskill - An implementation of the TrueSkill rating system for Python
webdiff - Two-column web-based git difftool
probability - Probabilistic reasoning and statistical analysis in TensorFlow
locust - "git diff" over abstract syntax trees
Keras - Deep Learning for humans
unison - A friendly programming language from the future