pyro
jupyterlab-git
| pyro | jupyterlab-git | |
|---|---|---|
| 9 | 7 | |
| 8,364 | 1,394 | |
| 0.5% | 1.0% | |
| 8.4 | 7.7 | |
| 11 days ago | 17 days ago | |
| Python | TypeScript | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
jupyterlab-git
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The Jupyter+Git problem is now solved
- GitHub PR code reviews with ReviewNB[4]
Alternatively, if you don't care about cell outputs then Jupytext[5]
Disclaimer: I built ReviewNB. It's a completely bootstrapped business, 5 years in the making and now used by leading DS teams at Meta, AWS, NASA JPL, AirBnB, Lyft, Affirm, AMD, Microsoft & more (https://www.reviewnb.com/#customers)
[1] https://github.com/jupyterlab/jupyterlab-git
I use this plugin for my jupyter notebook git integration. It has a git diff option that's useful but gets very slow for complex documents. Perhaps under the hood it's using one of the other tools mentioned in the postscript.
https://github.com/jupyterlab/jupyterlab-git
- Ask HN: Are there any good Diff tools for Jupyter Notebooks?
- Best extensions for JupyterLab!!
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Git extension for JupyterLab 3 released. Node/build step no longer needed (see updated install instructions). Adds commit & push, file browser context menu integration, Ctrl + enter to commit, "update diff" button and more!
Change log for this release: https://github.com/jupyterlab/jupyterlab-git/releases/tag/v0.30.0
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Recommendations for co-working on Jupyter Notebooks
Also there is an awesome jupyterlab-git extension.
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[D] Official Jupyter survey. How can Jupyter bet fit your workflow?
Official git extension https://github.com/jupyterlab/jupyterlab-git
What are some alternatives?
PyMC - Bayesian Modeling and Probabilistic Programming in Python
jupyterlab-spreadsheet-editor - JupyterLab spreadsheet editor for tabular data (e.g. csv, tsv)
scikit-learn - scikit-learn: machine learning in Python
debugger - A visual debugger for Jupyter notebooks, consoles, and source files
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
JupyterLab - JupyterLab computational environment.
trueskill - An implementation of the TrueSkill rating system for Python
jupyterlab-desktop - JupyterLab desktop application, based on Electron.
probability - Probabilistic reasoning and statistical analysis in TensorFlow
nbdime - Tools for diffing and merging of Jupyter notebooks.
Keras - Deep Learning for humans
qgrid - An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks