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- Changelog Media
- Media Type |
- audio
- Podknife tags |
- Artificial Intelligence,
- Business,
- Data Science,
- Interview,
- Machine Learning,
- Tech News,
- Technology
- Publication Date |
- Oct 20, 2020
- Episode Duration |
- 00:48:27
Rajiv Shah teaches Daniel and Chris about data leakage, and its major impact upon machine learning models. It’s the kind of topic that we don’t often think about, but which can ruin our results. Raj discusses how to use activation maps and image embedding to find leakage, so that leaking information in our test set does not find its way into our training set.
Rajiv Shah teaches Daniel and Chris about data leakage, and its major impact upon machine learning models. It’s the kind of topic that we don’t often think about, but which can ruin our results. Raj discusses how to use activation maps and image embedding to find leakage, so that leaking information in our test set does not find its way into our training set.
Rajiv Shah teaches Daniel and Chris about data leakage, and its major impact upon machine learning models. It’s the kind of topic that we don’t often think about, but which can ruin our results. Raj discusses how to use activation maps and image embedding to find leakage, so that leaking information in our test set does not find its way into our training set.
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Featuring:
- Rajiv Shah – Twitter, GitHub, LinkedIn, Website
- Chris Benson – Twitter, GitHub, LinkedIn, Website
- Daniel Whitenack – Twitter, GitHub, Website
Show Notes:
Something missing or broken? ai-109.md">PRs welcome!
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