Why he quit a $500k+ machine learning job at Meta (Facebook): a candid review of his experience, mistakes, and ML best practices - Damien Benveniste

1

Introduction

00:00 • 2min

2

The Beginning of Machine Learning

02:22 • 5min

3

How Did You Get Into Meta?

07:13 • 4min

4

Is That the Right Job for Me?

11:38 • 4min

5

Using Machine Learning in Ads

15:30 • 5min

6

Is There an Alto M L Solution?

21:00 • 3min

7

Automating Machine Learning Training

24:22 • 3min

8

A Modo Paradime, a Reck Engine

27:40 • 5min

9

Meta - What Was It Like to Work at Meta?

32:40 • 6min

10

The Impact of Machine Learning in Ads

38:10 • 3min

11

Is There a Balance Between Short and Long Term Projects?

41:15 • 3min

12

What You Learned From Meta?

44:04 • 5min

13

I'm Not Happy in My Company

49:30 • 2min

14

Ameta - What Projects Have Shaped Your Career?

51:28 • 4min

15

The Concept of Competition

55:16 • 2min

16

Using Time Boxes to Produce Value Quickly

57:16 • 3min

17

How to Get a Job as a Junior Deda Scientist

01:00:07 • 3min

18

Do You Have a Base Line for Machine Learning?

01:03:34 • 3min

19

Measuring Your Impact

01:06:17 • 3min

20

You Need to Deliver Value Quickly

01:09:11 • 3min

21

Time Boxing in Machine Learning

01:11:51 • 5min

22

The Importance of Adapting to Data Changes

01:16:23 • 4min

23

Learning Is Teamwork, You Know?

01:20:06 • 3min

24

The Most Challengesome Project You Have Worked On?

01:23:19 • 5min

25

Machine Learning Is Good at Doing

01:28:29 • 6min

26

The Unexpected Things You Learned From This Project

01:34:15 • 3min

27

Machinening Projects Are Iterative

01:37:05 • 2min

28

Developing a Model Into a Note Book

01:39:32 • 4min

29

Development Coding

01:43:03 • 3min

30

I'm a Data Scientist, I've Moved to a Jupiter Note Book

01:45:44 • 3min

31

Do You See Yourself as a Machine Learning Engineer?

01:48:47 • 2min

32

I Was Never a Sufte Engineer.

01:50:22 • 5min

33

Is There Something in the Masen Learning Community That Most People Contrast With?

01:54:57 • 3min

34

Is There a Bias in Lineal Regression?

01:58:24 • 2min

35

Machine Learning

02:00:50 • 5min

36

Are You a Data Scientist?

02:05:52 • 5min

37

I Was the Victim of the Job Title of Dela Science Shifting

02:10:28 • 1min

38

Machine Learning

02:11:52 • 2min

39

Machine Learning Is a Great Place for You to Be

02:13:59 • 2min

40

How to Build a Business Around Machine Learning?

02:15:29 • 5min

41

Do People Want It?

02:20:02 • 3min

42

How Do You Lean on on a Controversial Topic?

02:22:35 • 3min

43

I Felt That I Was Not Heard in a Company That Cares a Lot About Their Employes

02:25:33 • 4min

44

The Future of Deep Learning

02:29:11 • 3min

45

Machine Learning Is Getting More and More Useful

02:31:57 • 3min

46

Machine Learning - More Specializations

02:35:20 • 4min

47

Are You Excited About Retiring?

02:39:30 • 2min

48

You Found Me. I Linked In

02:41:46 • 3min

Why he quit a $500k+ machine learning job at Meta (Facebook): a candid review of his experience, mistakes, and ML best practices - Damien Benveniste - the data scientist show049