Diverse Topics in ML
I am going to gather diverse topics regarding to ML, but I won’t discuss none of them. I gathered them because these are not technical topics per se, are more related to theory or part of the ecosystem.
When I will able to add more, I will do.
General:
- Machine Learning from Wikipedia
- AI transform playbook
- machine-learning-yearning
- statistical inference in one sentence
- data jujitsu
- Rules of ML - martin.zinkevich and summary here
- Problem Framing
- SE4ML
AI Literacy
MLOps
- MLOps: automation pipelines and CD in AI
- Hidden Technical Debt in ML Systems and summary here
- Automating the end-to-end lifecycle of Machine Learning applications - M. Fowler Blog
- A Brief Guide to Running ML Systems in Production
Agile
- Agile Machine Learning: Effective Machine Learning - Book
- Agile Ds 2.0- Book
- Practical DataOps: Delivering Agile Data Science at Scale - Book
- Machine Learning Systems: Designs that scale - Book
Ethics
- Ethics of Artificial Intelligence and Robotics - Stanford
- Ethics of AI: WIkipedia
- Ethics and Fairness - Yann LeCun & Timnit Gebru Discuss
- Institute of Ethical AI
- Ethical AI Services