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Stanford CS230 | Autumn 2025 | Lecture 10: What’s Going On Inside My Model?

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai December 2, 2025 This lecture covers what's happening inside your model and provides a class wrap-up. To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs230-deep-learning Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/ View the playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNRRGdS0rBbXOUGA0wjdh1X Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department

Kian Katanforooshhost
Dec 15, 20251h 46mWatch on YouTube ↗

Episode Details

EPISODE INFO

Released
December 15, 2025
Duration
1h 46m
Channel
Stanford Online
Watch on YouTube
▶ Open ↗

EPISODE DESCRIPTION

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai December 2, 2025 This lecture covers what's happening inside your model and provides a class wrap-up. To learn more about enrolling in this course, visit: https://online.stanford.edu/courses/cs230-deep-learning Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/ View the playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNRRGdS0rBbXOUGA0wjdh1X Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department

SPEAKERS

  • Kian Katanforoosh

    host

    Stanford CS230 instructor and deep learning educator.

EPISODE SUMMARY

In this episode of Stanford Online, featuring Kian Katanforoosh, Stanford CS230 | Autumn 2025 | Lecture 10: What’s Going On Inside My Model? explores interpreting CNNs and diagnosing frontier model training and behavior issues The lecture opens with a frontier-lab case study and organizes debugging evidence into four buckets: training/scaling telemetry, internal representations, data/distribution issues, and capability/safety evaluation results.

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