

#2: Deep Learning based Recommender Systems with Even Oldridge
12 snips Oct 31, 2021
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Introduction
00:00 • 2min
Recsus 2018 - What's Your Story?
02:26 • 3min
Is There a Difference Between Realtor and Plenty of Fish?
05:29 • 2min
Is There a Rexxas Framework?
07:12 • 4min
How Do the Dots Connect Backwards?
11:11 • 2min
Rexxus - What's the Biggest Challenge in the Rexis Space?
13:21 • 3min
Is There a Future for Deep Learning?
16:42 • 2min
Deep Learning Models Are Not Consistently Winning Recommender Systems Competitions
18:41 • 2min
Deep Learning Is Very Hard to Do Correctly
20:16 • 5min
Deep Learning
24:47 • 3min
NVIDIA - What Challenges Are You Trying to Solve?
28:08 • 3min
MV Tabular - A Machine Learning Tooling for Machine Learning
30:54 • 2min
Is Iterative Pre-Processing of Models a Good Idea?
32:49 • 3min
Envitabular - What Would You Really Like to Work With?
35:24 • 4min
The Cost of GPUs in Deep Learning Platforms
39:08 • 2min
The Biggest Challenge for Deep Learning Platforms
41:26 • 3min
Is There a Wish for the Raxxis Field?
44:43 • 2min
What's Your Favorite Product in the Large Space of Recommended Products?
46:16 • 3min