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 https://weightwatcher.ai/ ), which provides ways to test the quality and fit of deep neural networks without having to rely upon a validation datas...
The Prompt Desk · Justin Macorin, Bradley Arsenault
Audio is streamed directly from the publisher (audio.ausha.co) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
In this episode, we interview Charles H Martin about his open-source Weight Watcher project ( found here https://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: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link
Hosted on Ausha. See ausha.co/privacy-policy for more information.