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Munich DataGeeks

munichdatageeks
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Decks

Florian Haselbeck- Advancing Synthetic Protein Design with Large Language Models
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68
Tobias Ladner- Formal Verification of Neural Networks in Safety-Critical Environments
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87
Uladzislau Sazanovich - JetBrains AI: Deep Dive
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73
Thomas Schmidt - Revolutionizing SQL Data Model Testing: Introducing SQL-Mock by DeepL

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49
Jan Hauffa - A Case Study on Retrieval-Augmented Generation for Document Q&A: Experiences and Future Perspectives

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92
Maximilian Duesberg - The Data is Clear - But Humans are not

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97
Dr.Christoph Mittendorf-Beyond Bard and Transformers: Unconventional ML Use Cases
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140
Heidi Seibold - Are (data) scientists bad at science?
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130
Sebastian Schwarz- A Competitive Time-Trial AI for Need for Speed: Most Wanted Using Deep Reinforcement Learning
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170
Florian Pfisterer- Fairness in automated decision making
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65
Roland Rodde- Vegetation management for powerlines with remote sensing data
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150
Applying Model-Based Optimization to Hyperparameter Optimization in Machine Learning
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250
PILL/CANDY DEFECT DETECTION
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300
Gerrit Gruben: Limits of Data Science and other ethical considerations
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420
Ben Flood - Insurance Stuff for DataGeeks
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340
Michael Green: Deep probabilistic neural networks - A way forward
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430
Transfer Learning for Fun and Profit
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150
Word Embeddings - the Good, the Bad, and the Ugly
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170

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