Machine Learning in Production | ML Lessons from Duolingo, Uber, Netflix
In this session, we break down the foundations of Machine Learning Engineering and explore how strong planning and simple design lead to real-world success.
Topics Covered:
Key differences between a Data Scientist and a Machine Learning Engineer
Why simplicity reduces risk in ML projects
How to apply Agile fundamentals to machine learning workflows
DevOps vs MLOps — where they align, where they differ
Here is the link to Lecture 2 Notes : https://drive.google.com/file/d/1-TNF...