

🎓 MLOps lessons learned helping companies build their ML systems with Lee Harper, Lead DS at Catapult
Nov 4, 2021
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Introduction
00:00 • 2min
Tein, Machine Learning, a Nu Su Position
01:53 • 4min
Getting a Master's Degree in Machine Learning?
06:01 • 2min
Is There a Diversity of Backgrounds in Data Science?
08:08 • 4min
Is There a Major Shift in Production for Machine Learning?
12:07 • 2min
Is There a Common Use Case Right Now?
14:19 • 4min
Do You Think It's More Common in Data Science Than Soft Development?
18:34 • 2min
Goling Is the Single Most Important Skill in This Field
20:45 • 4min
Machine Learning - How Do You Enable Machine Learning?
25:13 • 2min
Is There a Solution for Scalable Cloud Computing?
27:41 • 4min
How to Start Up a Data Security Solution?
31:26 • 4min
Machine Lo Systems Responsibilities
35:24 • 3min
The Bar for Atonymous Pekles
38:30 • 1min
Is It Possible to Build a Fair Model?
39:58 • 2min
Ias Is Incoded in All Kinds of Ways
42:01 • 4min
The Challenges of Machine Learning in Production
46:14 • 2min
The Classic Kinof Errors
48:27 • 5min
Tooling Advice
53:10 • 2min
Yb E Wo on We Captis, I Dare Not.
55:17 • 4min
I've Been Using Windows for a While Now.
59:13 • 3min
What Happens Before I Start Working?
01:01:52 • 5min
Are You Building the Right Thing?
01:06:25 • 2min