LM101-080: Ch2: How to Represent Knowledge using Set Theory

from Learning Machines 101 · host Richard M. Golden

This particular podcast covers the material in Chapter 2 of my new book "Statistical Machine Learning: A unified framework" with expected publication date May 2020. In this episode we discuss Chapter 2 of my new book, which discusses how to represent knowledge using set theory notation. Chapter 2 is titled "Set Theory for Concept Modeling".

Episode metadata supplied by the publisher feed · Published Feb 29, 2020

Embed this episode

Attribution link and audio player

NOW PLAYING

LM101-080: Ch2: How to Represent Knowledge using Set Theory

0:00 31:43

1×

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

Share this episode

Similar Episodes

No similar episodes found.

Similar Podcasts

CISO Perspectives (public) N2K Networks This season on CISO Perspectives, host Kim Jones explores some of the challenges of leading through uncertainty. We explore the complexity of the changing nature of regulation and working with the federal government, the evolution of privacy and fraud, and how emerging technologies like AI and quantum computing are changing cyber. When you don’t know what questions to ask, you’re afraid to ask, or don’t know who to ask, CISO Perspectives provides the foundation for learning in this brave new world.

Frequently Asked Questions

How long is this episode of Learning Machines 101?

This episode is 31 minutes long.

When was this Learning Machines 101 episode published?

This episode was published on February 29, 2020.

Can I download this Learning Machines 101 episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.

URL copied to clipboard!