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2026/06/10 22:11 Lecture 10 - Experimental Design – emilian.radoi
2026/06/10 22:11 Lecture 07 - Regression models – emilian.radoi
2026/06/10 22:10 Lecture 06 - Comparing Systems – emilian.radoi
2026/06/10 22:10 Lecture 05 - Summarising Measured Data – emilian.radoi
2026/06/10 22:10 Lecture 04 - Workloads – emilian.radoi
2026/06/10 22:09 Lecture 03 - Common Mistakes & Metrics – emilian.radoi
2026/06/10 22:09 Lecture 02 - Charts – emilian.radoi
2026/06/10 22:08 Lecture 01 - Introduction – emilian.radoi
2026/06/10 19:51 General Information – emilian.radoi
2026/06/10 19:51 Annotation – emilian.radoi
2026/06/10 19:51 Competition – emilian.radoi
2026/06/10 19:51 Project – emilian.radoi
2026/06/10 19:50 Lecture 10 - Language Modelling – emilian.radoi
2026/06/10 19:50 Lecture 08 - Semi-/Self-Supervised Learning – emilian.radoi
2026/06/10 19:50 Lecture 06 - Segmentation and Object Detection – emilian.radoi
2026/06/10 19:50 Lecture 05 - Transformers – emilian.radoi
2026/06/10 19:50 Lecture 04 - CNN Architectures – emilian.radoi
2026/06/10 19:49 Lecture 03 - Classification with CNNs – emilian.radoi
2026/06/10 19:49 Lecture 02 - Neural Networks – emilian.radoi
2026/06/10 19:49 Lecture 01 - Introduction – emilian.radoi

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ep.txt · Last modified: 2026/03/02 00:48 by emilian.radoi

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