first-contributions
tensorflow
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| first-contributions | tensorflow | |
|---|---|---|
| 91 | 222 | |
| 35,317 | 182,456 | |
| 0.0% | 0.8% | |
| -20.8 | 10.0 | |
| 9 months ago | 4 days ago | |
| C++ | ||
| MIT License | 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.
first-contributions
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Merge Mastery: Elevating Your Pull Request Game in Open Source Projects
GitHub's First Contribution guide: A gentle intro to contributing to open-source.
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First Open-Source Contribution
We will contribute to the repository of "First contributions". You can go to the following link: https://github.com/firstcontributions/first-contributions
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What is Open Source & How to contribute to it?
First Contributions, EddieHub Issue Finder, goodfirstissue.dev, goodfirstissues.com, firsttimersonly.com.
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First Contributions: learn how to contribute to open source projects
First Contributions GitHub Repository
- Show HN: Make your first open source contribution in 5 minutes
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Tublian Internship Journey: Navigating the Internship Landscape in Week One
In the inaugural chapters of my Tublian journey, I found myself immersed in the realms of "First Contributions." True to its name, this project served as a welcoming gateway, designed with the noble purpose of simplifying the often complex landscape of contributing to open source endeavors, particularly for those taking their first steps into this vibrant community.
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Learn open-source contribution.
Recently i found a github repository to learn open-source contribution for beginners. Click here to view the repository.
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Hacktoberfest Pledge 🎉
You'll need to find a first contributions repository (I used this one), and from there it'll be pretty self-explanatory. Good luck - you'll do great!
- Show HN: Hands on tutorial for open source contribution
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?
CodeTriage - Discover the best way to get started contributing to Open Source projects
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）
awesome-for-beginners - A list of awesome beginners-friendly projects.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
good-first-issue - Make your first open-source contribution.
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
svelteui - SvelteUI Monorepo
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.
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
scikit-learn - scikit-learn: machine learning in Python
Blitz - ⚡️ The Missing Fullstack Toolkit for Next.js
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.