Open-source MLOps Fundamentals Course 🚀

Made With ML — Sun, 06 Nov 2022 15:02:07 +0000

Hi everyone, I’m the creator of Made With ML and I wanted to share that V1 of the open-source course is finally complete! We cover topics across data → modeling → serving → testing → reproducibility → monitoring → data engineering + more, all with the goal of teaching how to responsibly develop, deploy and maintain production ML applications.

🛠 Project-based
💡 Intuition (first principles)
💻 Implementation (code)
🏆 30K+ GitHub ⭐️ 
❤️ 40K+ community
✅ 49 lessons, 100% open-source

Find all the lessons here → https://madewithml.com/
MLOps course repo → https://github.com/GokuMohandas/mlops-course
Made With ML repo → https://github.com/GokuMohandas/Made-With-ML

[Background] I started Made With ML as a way for me to share my learnings from the different contexts I’ve brought ML to production in the past. I currently work closely with teams from early-stage/F500 companies, as well as collaborating with the best tooling/platform companies, to make delivering value with ML even easier and faster.

[Request] I keep all the lessons updated as I learn more (especially constantly evolving spaces such as testing and monitoring ML). But what are some modeling-agnostic topics that are missing here that are very crucial to production ML / MLOps? A few high priority ones on the TODO list include bias (identifying, mitigating), distributed workflows (not just for training), etc. What else should be added here?

DEV Community: Made With ML

Open-source MLOps Fundamentals Course 🚀