🛠 Building tools for MLOps with Guy Smoilovsky

1

Introduction

00:00 • 2min

2

Is This a Data Engineering Podcast?

01:34 • 3min

3

DAGSUB - The Origin of Deep Learning

04:26 • 6min

4

Open Source Workflow for Machine Learning

10:15 • 3min

5

DAGS and Machine Learning

13:36 • 4min

6

Machine Learning and MLOps - What's the Biggest Change?

17:14 • 4min

7

DevOps and MLOps

21:19 • 4min

8

ML and MLOps

25:15 • 6min

9

Is There a Way to Automate Deep Learning?

31:10 • 4min

10

MLOps - What Do You Think Are the Challenges in Machine Learning?

34:50 • 3min

11

Does Tool X Do DevOps for Me MLOps for Me?

38:05 • 5min

12

ML Platforms

42:51 • 3min

13

Machine Learning Is Progressing So Fast That You Shouldn't Attempt to Optimize It to the Last Drop

46:03 • 2min

14

What Do You Think About Version Control in Software Editing?

48:22 • 5min

15

Automate the Deployment of Machine Learning Models

53:20 • 5min

16

TDD and TDD in Software Development

57:51 • 2min

17

Is TDD a Test Driven Development?

59:51 • 5min

18

Machine Learning

01:05:20 • 5min

19

The Last Barrier to Real Superhuman Intelligence

01:10:00 • 2min

20

Quantum Resilient Encryption Isn't a Good Idea

01:12:29 • 2min

21

Using GPUs for Deep Learning in a Systematic Way

01:14:34 • 3min

22

What Should You Worry About?

01:17:10 • 4min