Software Engineering Radio - the podcast for professional software developers

Episode 493: Ram Sriharsha on Vectors in Machine Learning

Jan 4, 2022

39:59

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Highlights

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Episode notes

What Is Feature Engineering?

02:34

Using Tree Trained Modal Models in Deep Learning

02:03

Machine Learning

02:20

Introduction

2min

Tenser in Machine Learning?

2min

Machine Learning at Lower Precision Values?

2min

What Is Feature Engineering?

3min

Using Tree Trained Modal Models in Deep Learning

2min

Vector and Betting - Vector Search and Vector Data Bases

2min

Are We Always Searching for Similarity?

2min

Vector Search

2min

The Range of Scales of a Vector Search

2min

10.

Machine Learning - Distance Functions

2min

11.

Cosin Distance, Euclid Distance, and Chabishe Distance?

3min

12.

The Biggest Challenge With Distance Functions

2min

13.

How Do You Determine the Approximation of Nearest Neighbors?

2min

14.

Machine Learning

2min

15.

Cloud Elasticity - What Are the Challenges of Scaling Vector Search?

3min

16.

Scaling Scaling Machine Learning Applications

2min

17.

The Challenges of a Search Application Developer?

2min

18.

Pine Condaro - What Are the Trends in Machine Learning?

3min

Ram Sriharsha of Pinecone discusses the role of vectors in machine learning, a technique that lies at the heart of many of the machine learning applications we use every day. Host Philip Winston spoke with Sriharsha about the basics of vectors, vector...