LM101-031: How to Analyze and Design Learning Rules using Gradient Descent Methods (RERUN)

In this rerun of Episode 16, we introduce the important concept of gradient descent which is the fundamental principle underlying learning mechanisms in a wide range of machine learning algorithms. Check out the transcripts of this episode and related references and software at: www.learningmachines101.com !!!

Episode metadata supplied by the publisher feed · Published Jun 21, 2015

Embed this episode

Attribution link and audio player

NOW PLAYING

LM101-031: How to Analyze and Design Learning Rules using Gradient Descent Methods (RERUN)

0:00 32:02

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 32 minutes long.

When was this Learning Machines 101 episode published?

This episode was published on June 21, 2015.

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!