• 设为首页
  • 点击收藏
  • 手机版
    手机扫一扫访问
    迪恩网络手机版
  • 关注官方公众号
    微信扫一扫关注
    迪恩网络公众号

gimseng/99-ML-Learning-Projects: A list of 99 machine learning projects for anyo ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

gimseng/99-ML-Learning-Projects

开源软件地址(OpenSource Url):

https://github.com/gimseng/99-ML-Learning-Projects

开源编程语言(OpenSource Language):

Jupyter Notebook 100.0%

开源软件介绍(OpenSource Introduction):

99-ML-Learning-Projects

A list of 99 machine learning projects for anyone interested to learn machine learning from coding and building projects.

Our working philosophy is to provide a curated repo for anyone to contribute a cool/fun exercise and solution that is useful for anyone (including themselves) in their journey of learning machine learning.

Getting Started

The format is roughly the following:

  1. Propose an exercise by creating an issue ticket and write what you think is an useful coding exercise for certain concepts.

  2. If enough people are interested in that issue ticket, hopefully either you or someone else will write the exercise statement properly similar to the style of a lab exercise/homework question.

  3. Then someone will fork the repo, write up their solution, with a bit of polish and documentation, submit a pull request. Please see general contribution guidelines for more details on how to contribute solutions.

  4. Some of us will scrutinize the codes, review, make suggestions and eventually include (merge) them into the main project repo.

  5. At anytime, someone can repeat suggest improvements/changes to 3-4 above for a particular exercise. This is done by creating an issue ticket for improvement/enhancement. One can then repeat 3-4.

  6. Finally, repeat 1-5 indefinitely till we hit 99/99 projects.

Please abide by code of conduct guidelines to have an open and friendly open source collaboration.

Goal: 99 Projects

Current: 10 Projects

Table of Contents

General-Purpose Machine Learning

Computer Vision

Natural Language Processing

Bayesian

Misc/Mix Models

Refreshers/Cheatsheets

Dependencies

Some of the libraries (and their versions) we are using:

  • Python (>= 3.6)
  • NumPy (>= 1.18.5)
  • Pandas (>= 1.0.5)
  • Matplotlib (>= 3.2.2)
  • Seaborn (>= 0.10.1)
  • Scikit-learn (>= 0.22.2)
  • Tensorflow (>= 2.2.0)
  • PyTorch (>= 1.5.1)

Help and Support

If you want to get in touch with us, say hi on our discord/gitter chatroom:

Recent Contributors

Credit:

This project is inspired by Unnit Metaliya’s answer on quora: https://qr.ae/pNK0FW

For credits, these are the two repos (one for C and one for React) where I got the idea from:

License

This repo is covered under The MIT License.




鲜花

握手

雷人

路过

鸡蛋
该文章已有0人参与评论

请发表评论

全部评论

专题导读
上一篇:
CodeKal/HacktoberFest2018: HacktoberFest 2018 CodeKAL发布时间:2022-06-24
下一篇:
mautic/mautic: Mautic: Open Source Marketing Automation Software.发布时间:2022-06-24
热门推荐
阅读排行榜

扫描微信二维码

查看手机版网站

随时了解更新最新资讯

139-2527-9053

在线客服(服务时间 9:00~18:00)

在线QQ客服
地址:深圳市南山区西丽大学城创智工业园
电邮:jeky_zhao#qq.com
移动电话:139-2527-9053

Powered by 互联科技 X3.4© 2001-2213 极客世界.|Sitemap