Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Introduction
00:00 • 5min
The Weather in Palo Alto
05:17 • 2min
The Infinite Corridor at MIT
06:58 • 3min
How to Take Your PhD Project and Turn It Into a Business
09:55 • 2min
Automated Data Visualization
11:29 • 2min
How I Changed My Focus to Machine Learning
13:06 • 3min
How to Track and Reproduce Models
16:18 • 2min
How to Track Variations in Python Models
17:56 • 2min
How Model DB Can Help You Build a Business With It
19:26 • 4min
How to Transition From PhD Work to Starting a Business
23:35 • 2min
Building a Team Around Model DB
25:13 • 2min
The Importance of Data Science in Productivity
26:59 • 2min
The Importance of Data Science Maturity
28:39 • 2min
The Top 3 Areas Where Data Science Teams Are Investing
30:14 • 2min
How to Get Product Buy-in for Your Data Science Model
32:11 • 4min
The Importance of Documenting Data Transformations
36:11 • 3min
How to Maintain a Data Science Model
39:04 • 2min
How Verta Fits in With Data Science Teams
40:55 • 2min
The Importance of Monitoring and Maintenance in Data Science
42:34 • 2min
The Future of Data Science
44:31 • 2min
The Future of Machine Learning
46:39 • 2min
The Future of Machine Learning
48:32 • 2min
How to Be a Successful Data Scientist
50:18 • 2min
How to Be a Successful Software Engineer
52:43 • 2min
How to Be a Data Scientist at Data Science Go 2019
54:19 • 2min