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Data-free Quality Analysis of Deep Neural Nets with Charles H. Martin
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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.
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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
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52 episodes
Fetch error
Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on January 04, 2025 16:10 ()
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 394618454 series 3519364
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 by Ausha. See ausha.co/privacy-policy for more information.
52 episodes
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