BT
You are now in FULL VIEW
CLOSE FULL VIEW

Interpretable Machine Learning Products
Recorded at:

| by Mike Lee Williams Follow 0 Followers on Jun 06, 2018 | NOTICE: The next QCon is in New York Jun 25 - 29, 2018. Join us!
38:37

Summary
Mike Lee Williams discusses how interpretability can make deep neural networks models easier to understand, and describes LIME, an open source tool that can be used to explore what machine learning classifiers (or models) are doing.

Sponsored Content

Bio

Mike Lee Williams does applied research into computer science, statistics and machine learning at Cloudera Fast Forward Labs. While getting his PhD in astrophysics he spent 2% of his time observing the heavens in beautiful far west Texas, and the other 98% trying to figure out how to fit straight lines to data. He once did a postdoc at the Max Planck Institute for Extraterrestrial Physics.

QCon.ai is a AI and Machine Learning conference held in San Francisco for developers, architects & technical managers focused on applied AI/ML.

Login to InfoQ to interact with what matters most to you.


Recover your password...

Follow

Follow your favorite topics and editors

Quick overview of most important highlights in the industry and on the site.

Like

More signal, less noise

Build your own feed by choosing topics you want to read about and editors you want to hear from.

Notifications

Stay up-to-date

Set up your notifications and don't miss out on content that matters to you

BT