pyro
tensorflow
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pyro | tensorflow | |
---|---|---|
9 | 222 | |
8,356 | 182,456 | |
0.9% | 0.8% | |
8.4 | 10.0 | |
6 days ago | 3 days ago | |
Python | C++ | |
Apache License 2.0 | Apache License 2.0 |
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.
tensorflow
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Google lays off its Python team
[3]: https://github.com/tensorflow/tensorflow/graphs/contributors
- TensorFlow-metal on Apple Mac is junk for training
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐
- One .gitignore to rule them all
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10 Github repositories to achieve Python mastery
Explore here.
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GitHub and Developer Ecosystem Control
Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.
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Non-determinism in GPT-4 is caused by Sparse MoE
Right but that's not an inherent GPU determinism issue. It's a software issue.
https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.
Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.
Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.
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Can someone explain how keras code gets into the Tensorflow package?
and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:
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Is it even possible to design a ML model without using Python or MATLAB? Like using C++, C or Java?
Exactly what language do you think TensorFlow is written in? :)
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How to do deep learning with Caffe?
You can use Tensorflow's deep learning API for this.
What are some alternatives?
PyMC - Bayesian Modeling and Probabilistic Programming in Python
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
scikit-learn - scikit-learn: machine learning in Python
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
trueskill - An implementation of the TrueSkill rating system for Python
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
probability - Probabilistic reasoning and statistical analysis in TensorFlow
Keras - Deep Learning for humans
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.