The MLOps Podcast

🤹‍♀️ Building models that actually perform with Kyle Gallatin

Jun 20, 2022

58:21

Creator website

Highlights

AI Chapters

Episode notes

Is Machine Learning the First Step?

02:33

Having a Data Scientist and a Machine Learning Team?

02:43

Tensorflow

02:28

Introduction

2min

Data Science - What a Unique Path?

2min

Is It a Prerequisite to Getting Into Machine Learning?

3min

Machine Learning Platform at Etse

2min

What's the Definition of the EME Platform?

2min

Is There a Split Between Data Science and Training?

3min

Tensorflow

2min

The Experimentation Side of Machine Learning?

3min

Having a Data Scientist and a Machine Learning Team?

3min

10.

Is Machine Learning the First Step?

3min

11.

Is It the Platform Team or the Data Scientist?

3min

12.

How Do You Preserve Your Knowledge?

2min

13.

Is There a Trade-Off Between Performance and the Results?

3min

14.

How Do You Build in Machine Learning Profiles?

3min

15.

Machine Learning Is Just Like Soft Development

2min

16.

Are You Prescriptive With Tensorflow?

2min

17.

Machine Learning Infrestructure

3min

18.

Scaling Machine Learning - Is Scaling the Right Thing?

2min

19.

The Scale of Data, the Scales of Models

2min

20.

Lie, Is There a Recurring Theme for Machine Learning?

2min

21.

Is It a Good Idea to Work With Cobenets?

3min

22.

Doctor in Coubernetes for Machine Learning

3min

23.

Are You Curious About Something?

4min

In this episode, I had the pleasure of speaking with Kyle Gallatin, a Machine Learning Software Engineer at Etsy. We talk about how he built the machine learning platform at Etsy, experimentation in production (yes, you heard right), and how to optimize model performance at very large scales. It was awesome, and I'm sure many of you can learn a ton from this one!

Join our Discord community: https://discord.gg/tEYvqxwhah

Relevant Links:
➡️ Kyle on LinkedIn – https://www.linkedin.com/in/kylegallatin/

🌐Check Out Our Website! https://dagshub.com

Social Links:
LinkedIn: https://www.linkedin.com/company/dagshub
Twitter: https://twitter.com/TheRealDAGsHub
Dean Pleban: https://twitter.com/DeanPlbn