Data-free Quality Analysis of Deep Neural Nets with Charles H. Martin

In this episode, we interview Charles H Martin about his open-source Weight Watcher project ( found here weightwatcher.ai ), which provides ways to test the quality and fit of deep neural networks without having to rely upon a validation dataset. Given the scarcity of high-quality data and the complexity of modern multi-stage ML training and deployment pipelines, this technique could prove to be extremely valuable to any AI engineer, and we were interested to learn more.
—
Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.
Check out PromptDesk.ai for an open-source prompt management tool.
Check out Brad’s AI Consultancy at bradleyarsenault.me
Add Justin Macorin and Bradley Arsenault on LinkedIn.

Please fill out our listener survey here to help us create a better podcast: docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zRO…

Hosted on Ausha. See ausha.co/privacy-policy for more information.