Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Introduction
00:00 • 2min
The Difference Between Traditional and Machine Learning Models
01:31 • 3min
Machine Learning - What Are the Similarities and Differences?
04:17 • 5min
How to Deploy Machine Learning Models in the Wild?
09:17 • 3min
Using on Line Models to Make a Better Prediction
12:13 • 4min
The Business Case of Modeling Churn Risk Scores
15:43 • 2min
What if Instead of States, We Would Predict Actions?
17:31 • 5min
The Machine Learning Approach to Machine Learning
22:36 • 1min
Reinforcement Learning for Dynamic Pricing
23:55 • 3min
Is There a Difference Between a Micro Service and an API?
27:21 • 3min
Machine Learning
30:33 • 2min
Can Machine Learning Be Used to Automate Marketing?
32:48 • 4min
How to Make a Blended Whisky?
36:41 • 3min
How to Build a Discriminative Model?
39:20 • 3min
Machine Learning and Optimization
41:51 • 5min