🎨 Stable Diffusion and generative models with David Marx

1

Introduction

00:00 • 3min

2

How Do You Get Into Machine Learning?

02:47 • 4min

3

Exactly. Good Developers Shouldn't Be Lazy, Right?

06:19 • 4min

4

Coursera - Should I Go to Grad School?

09:55 • 2min

5

Getting Into a Data Science Consulting Firm After Grad School

12:17 • 3min

6

I'm the Machine Learning That Is Going to Automate You Away

15:15 • 3min

7

Data Scientist - Data Scientist Role in an Organization

18:28 • 2min

8

Is There a Constant in the Way That You Describe Your Path?

20:20 • 3min

9

Are You a Researcher?

23:26 • 4min

10

Is Good Enough the Best Way to Go?

27:27 • 2min

11

Is There a Cure of Specialization in Machine Learning?

29:46 • 3min

12

I Was a Data Scientist, I Should Just Buy My Own GPU

32:36 • 4min

13

The Clip Plus VQgan Technique

36:12 • 3min

14

Open Source Machine Learning - What Do You Need to Be Able to Contribute?

39:11 • 5min

15

Deep Learning

43:48 • 2min

16

The Stable Diffusion API

46:16 • 5min

17

Using Classifier Free Guidance

51:07 • 3min

18

How Do You Develop the Skills That You Need to Be a Data Scientist?

53:44 • 6min

19

I'm Just Learning for the Sake of Learning

59:32 • 3min

20

Is Stable Diffusion Still Python?

01:02:41 • 3min

21

Do You Have Any Counterintuitive Challenges With GPU Inference?

01:05:40 • 4min

22

Is Open Source a Good Way to Learn?

01:10:03 • 2min

23

IKEA Lego Sets - Is That a Tree House or an Ewoks?

01:12:19 • 2min