Practical AI: Machine Learning, Data Science, LLM

MLOps is alive and well

Feb 7, 2023

56:54

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Highlights

AI Chapters

Episode notes

MLOps Is a Machine Learning Model in Production

01:37

What Happens When Models Are Generated by Systems?

01:40

What's Next for AI?

01:34

Introduction

2min

What Is MLOps?

2min

Deep Learning and MLOps - What's the Difference?

2min

What Is MLOps?

2min

MLOps Is a Machine Learning Model in Production

2min

MLOps

2min

What Are You Guys Talking About?

2min

Machine Learning Plus Ops Versus Experiment Tracking

3min

ML Ops Is a Lies or Is It a Liar?

3min

10.

Chat GPT

2min

11.

ML Ops

2min

12.

Is There a Meta Layer?

2min

13.

Are They the Same or Are They Different?

2min

14.

I Don't Think That's Too Far

2min

15.

What's Next for AI?

2min

16.

Can We Personalize Episodes of Rick and Morty?

2min

17.

ChangeLog++

3min

18.

Detecting AI Generated Content

2min

19.

What Happens When Models Are Generated by Systems?

2min

20.

Having an MLOps Community for a Long Time

2min

21.

MLOps Engineer - What Do You Think Will Be Next?

3min

22.

How Do Different Organizations Think About MLOps?

2min

23.

You Are Not Google - Is That a Good Thing?

3min

24.

You Can't Do MLOps the Way Google Does

3min

25.

Is There an Oversimplification of the Market?

3min

26.

MLOps and the Language Model Chaining

2min

27.

The Gardner Hype Cycle

2min

28.

Practical AI Plus MLOps Community Podcast

2min

Worlds are colliding! This week we join forces with the hosts of the MLOps.Community podcast to discuss all things machine learning operations. We talk about how the recent explosion of foundation models and generative models is influencing the world of MLOps, and we discuss related tooling, workflows, perceptions, etc.

Join the discussion

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