Software Engineering Radio - the podcast for professional software developers

Episode 493: Ram Sriharsha on Vectors in Machine Learning

Jan 4, 2022
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Episode notes
1
Introduction
00:00 • 2min
2
Tenser in Machine Learning?
02:08 • 2min
3
Machine Learning at Lower Precision Values?
03:44 • 2min
4
What Is Feature Engineering?
06:00 • 3min
5
Using Tree Trained Modal Models in Deep Learning
08:33 • 2min
6
Vector and Betting - Vector Search and Vector Data Bases
10:37 • 2min
7
Are We Always Searching for Similarity?
12:52 • 2min
8
Vector Search
14:25 • 2min
9
The Range of Scales of a Vector Search
16:53 • 2min
10
Machine Learning - Distance Functions
19:12 • 2min
11
Cosin Distance, Euclid Distance, and Chabishe Distance?
21:31 • 3min
12
The Biggest Challenge With Distance Functions
24:09 • 2min
13
How Do You Determine the Approximation of Nearest Neighbors?
25:45 • 2min
14
Machine Learning
27:31 • 2min
15
Cloud Elasticity - What Are the Challenges of Scaling Vector Search?
29:51 • 3min
16
Scaling Scaling Machine Learning Applications
32:40 • 2min
17
The Challenges of a Search Application Developer?
35:09 • 2min
18
Pine Condaro - What Are the Trends in Machine Learning?
37:21 • 3min