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
Introduction
00:00 • 3min
How Do You End Up With a No Drug Candidate?
03:12 • 2min
Oncology
05:32 • 3min
Can You Predict the Function of a Protein?
08:57 • 2min
Are You Predicting the Functionality of a Drug?
10:37 • 4min
Deep Learning
14:57 • 2min
Do You Think You Can Be the Best at Machine Learning?
17:16 • 3min
A Scalable Approach to Machine Learning?
20:45 • 2min
Is There a Black Box Approach?
22:56 • 3min
Investing in Data Collection Versus Collecting More Data?
25:34 • 2min
Wet Labs - What's the Difference?
27:08 • 2min
How Do We Collect Meaningful Data From a Wet Lab?
28:57 • 3min
Is There a Soft Ware Solution That Will Help You Track Your Data?
31:32 • 2min
Do You Think M L Will Be Able to Predict Clinical Trials?
33:14 • 2min
How to Grow a Revenue Base in a Market Like That?
35:27 • 2min
Is the Academic Community Relevant?
37:25 • 2min
Is There a Capacity to Learn?
39:41 • 2min
Machine Learning - What's the Difference Between Biology and Aelab Scientist?
41:33 • 2min
A, A, It's an Opportunity of a Lifetime to Be a Part of the Intersection of Something Like This
43:32 • 2min
What's the Underrated Side of M L Ah?
45:22 • 4min
Is Multi Task Learning a Good Approach?
48:58 • 2min
Ai Shaim, Really Carious to Get Your Sake on This One.
50:44 • 2min
The Unexpected Hiding Blocks
52:48 • 3min