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Add tutorial 14: evaluation done right, the point-adjust trap ci #11: Commit 5dfa8bd pushed by JulienAu
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Add tutorial 13: foundation models and zero-shot detection ci #10: Commit 3635f77 pushed by JulienAu
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Add tutorial 12: streaming detection with the Robust Random Cut Forest ci #9: Commit bde31e3 pushed by JulienAu
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Add tutorial 11: self-supervised representations, detecting without r… ci #8: Commit 364e3f7 pushed by JulienAu
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Add tutorial 10: transformers, when a better reconstruction detects w… ci #7: Commit 2a61d74 pushed by JulienAu
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Add tutorial 09: graph neural networks, predict from neighbours not f… ci #6: Commit f8a7616 pushed by JulienAu
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Add tutorial 07: VAEs, and what the likelihood actually buys ci #5: Commit a2b3bf9 pushed by JulienAu
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Add tutorial 06: forecasting residuals, without the lever it does not… ci #4: Commit 8e17c53 pushed by JulienAu
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Graph Update: pip in /. #1517976773 Dependency Graph #3: by dependabot Bot
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Add tutorial 05: matrix profile discords, expand the curriculum to 15… ci #3: Commit a1219e1 pushed by JulienAu
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Graph Update: pip in /. #1517901266 Dependency Graph #2: by dependabot Bot
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Add tutorial 04: USAD adversarial autoencoders, measured honestly ci #2: Commit 0b6c8bb pushed by JulienAu
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Add tutorial 03: anomaly detection with autoencoders ci #1: Commit 80b4518 pushed by JulienAu
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Graph Update: pip in /. #1517759610 Dependency Graph #1: by dependabot Bot
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