✍️ Building ML Teams and Platforms with Assaf Pinhasi

1

Introduction

00:00 • 5min

2

Machine Learning and Machine Learning - What I Learned From PayPal

05:17 • 2min

3

How Did It All Work?

07:06 • 3min

4

The ETL Approach to Modeling and Model Monitoring

10:05 • 3min

5

Is There a Comparative Approach to Cloud Platforms?

13:09 • 2min

6

Deep Learning - What Is It All About?

15:21 • 3min

7

Zebra

18:17 • 2min

8

Transition to Unstructured Data

19:58 • 5min

9

The Biggest Botanical Combination

24:30 • 4min

10

What Do You Do in Your Day to Day?

28:19 • 2min

11

Machine Learning and Production at Scale

30:13 • 4min

12

Machine Learning Is a System Level Optimization Process

34:39 • 2min

13

Scale and Data Six

36:57 • 5min

14

DevOps

42:25 • 3min

15

The Core Tenets of Machine Learning and Production

45:50 • 6min

16

I Think the Iterate Fast Part Is Really Important for Data Scientists

51:30 • 4min

17

The Role of the Team in Machine Learning

55:43 • 3min

18

Machine Learning and MLOps - What's Next?

58:32 • 2min

19

Is There a Consolidation of Tools and Platforms in Machine Learning?

01:00:46 • 2min

20

Machine Learning Platforms

01:02:59 • 2min

21

Chat GPT - The Future of Machine Learning

01:05:07 • 3min

22

Machine Learning

01:08:20 • 5min

23

Is There a Way to Automate Product Development?

01:12:59 • 2min

24

Machine Learning

01:14:44 • 3min