applied-ml
996.ICU
applied-ml | 996.ICU | |
---|---|---|
13 | 70 | |
25,984 | 267,482 | |
- | - | |
3.0 | 0.0 | |
5 days ago | 11 months ago | |
Rust | ||
MIT License | 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.
applied-ml
-
[D] Favorite ML Youtube Channels/Blogs/Newsletters
Also, have any of you stumbled across any cool GitHub repos like this one: https://github.com/eugeneyan/applied-ml ?
- Curated Papers on Machine Learning in Production
-
Top Github repo trends in 2021
The second repo I LOVE is Eugene Yan’s Applied ML repository. This is a brilliant idea to create and actually something I was planning on sort of casually doing in my non-existent free time… Anyhow, it is a curated list of technical posts from top engineering teams (Netflix, Amazon, Pinterest, Linkedin, etc.) detailing how they built out different types of AI/ML systems (e.g. forecasting, recommenders, search and ranking, etc.). Ofc, it focuses on AI/ML, but something similar could be made for the traditional or BI-oriented analytics stack, as well as the streaming world, super high value for practitioners! Btw-one of my favorite things at BCG used to be looking at our IT architecture team’s reference architecture diagrams… the best way to understand technologies is to look at how a ton of stuff is architected… and its fun!
- Curated papers, articles, & blogs on data science and ML in production
-
Messed up my career by pivoting to DS. Wondering if it's too late to switch to MLE
Applied ML: A collection of papers, articles, and blogs on ML in production by different companies (Netflix, Uber, Facebook, LinkedIn, etc)
-
[D] A dilemma of an ML guy in industry
Eugene Yan's applied-ml has tons of case studies.
- Papers & tech blogs by companies sharing their work on data science & machine learning in production.
-
My information dump for people trying to break into data science/interview notes
https://github.com/eugeneyan/applied-ml You may find some of his links interesting. I would avoid anything that refers to scaling up a platform as these are more backend engr focus. The more relevant posts to you are probably on the scale of blog posts that are product oriented like the ones I listed in section 4 (e.g. we wanted to solve X for our users and this is how we scoped and defined it). The technical aspects should come backseat to the business aspects. There's def a lot of companies/blog posts that he missed, but the internet is huge.
-
[D] Can anyone point me to resources/case studies of companies/business creating infrastructure for their data needs?
Check the resources mentioned in applied-ml. It includes blog posts/papers from many companies describing how they built some ML product X.
-
What content would be useful to intermediate Data Scientist
Check out this repo. They collect hundreds of case studies, broken down by dozens of methodologies from large real-world companies such as AirBnB, Nvidia, Uber, Netflix etc.
996.ICU
-
Help me understand the boomer mentality in Australia of wanting young people to struggle and slave like they did.
Then it was cracked down by the government. The creator of the 996ICU https://github.com/996icu/996.ICU was put into prison for treason.
- 狗逼粉红到我的YouTube下面留言,说996发起人判刑不是应为996项目。我没忍住骂了一顿。
- 996.ICU推动者被捕后妻子发声 却被墙国程序员集体围攻
- 996.ICU的发起人并非程渊
- 简要分析 ‖ 996·ICU发起人被捕案情简述和分析 加粗几点没有注意提及的地方 如佳士工人维权事件的影响没人注意
- 反996运动发起人勾结境外势力,涉嫌颠覆国家政权罪判处有期徒刑五年
- 996.ICU 项目发起人程渊的判决书(颠覆国家政权罪,2021年7月20日)
- 996.ICU项目发起人程渊被判刑了,罪名是 颠覆国家政权 是真的,这国家还能有好么?方丈小心眼,小垃圾,玩不起。
- What are your personal experiences working in IT in China?
-
Dangers at working an American branch of a chinese company?
Work life balance. TikTok/ByteDance is pretty well known for 996 work culture. And you will have to adapt to zoom calls from China and lots of docs/messages will have some blend of Chinese. Probably won't help with future promotions internally if you don't know Chinese. Google Translate is a must.
What are some alternatives?
awesome-mlops - A curated list of references for MLOps
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
awesome-ml-blogs - Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
machine-learning-roadmap - A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
freeCodeCamp - freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.
Cookbook - The Data Engineering Cookbook
git-issue - Git-based decentralized issue management
ml-surveys - 📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
gov-takedowns - Text of government takedown notices as received. GitHub does not endorse or adopt any assertion contained in the following notices.
pipebase - data integration framework
DeepFaceLab - DeepFaceLab is the leading software for creating deepfakes.