Sources and Docker Environment for the AI Lab at HSKA: https://www.iwi.hs-karlsruhe.de/iwii/info/module/INFM/7/INFM210ML#INFM212ML
Datum | Thema | Inhalt | Präsenz |
---|---|---|---|
15. November. | Allg. | Transformers + Projektintros | No |
22. November. | Allg. | Projektassignments | No |
29. November. | Allg. | No | |
6. Dezember. | Allg. | No | |
13. Dezember. | Allg. | No | |
20. Dezember. | Allg. | No | |
Allg. | Public Holidays | No | |
10. Januar. | Allg. | No | |
17. Januar. | Allg. | Final Presentation | Yes |
Semeval Numeval - quantitative understanding of English https://sites.google.com/view/numeval/numeval https://sites.google.com/view/numeval/data
https://competitions.codalab.org/competitions/33835
https://pan.webis.de/semeval23/pan23-web/clickbait-challenge.html
https://github.com/yogeshkumarpilli/Kaggle-NLP-Challenge https://www.kaggle.com/c/defi-ia-insa-toulouse/overview
https://www.kaggle.com/competitions/feedback-prize-effectiveness
https://www.kaggle.com/competitions/contradictory-my-dear-watson
https://www.kaggle.com/c/nbme-score-clinical-patient-notes/overview/code-requirements
"build a machine learning model that predicts which Tweets are about real disasters and which one’s aren’t." https://www.kaggle.com/c/nlp-getting-started/overview
"build a classifier that predicts whether or not a question will be closed given the question as submitted, along with the reason that the question was closed" https://www.kaggle.com/c/predict-closed-questions-on-stack-overflow/
"predict which of the provided pairs of questions contain two questions with the same meaning" https://www.kaggle.com/c/quora-question-pairs/data
https://www.kaggle.com/c/tweet-sentiment-extraction/overview "which words actually lead to the sentiment description? In this competition you will need to pick out the part of the tweet (word or phrase) that reflects the sentiment."
https://www.kaggle.com/competitions/movie-review-sentiment-analysis-kernels-only/overview "This competition presents a chance to benchmark your sentiment-analysis ideas on the Rotten Tomatoes dataset. You are asked to label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive."
https://www.kaggle.com/competitions/image-matching-challenge-2024/overview
https://www.kaggle.com/competitions/computer-vision-xm/overview
https://www.kaggle.com/competitions/internal-waves/overview
RSNA 2024 Lumbar Spine Degenerative Classification [detection, multiclass classification, incomplete labels]
https://www.kaggle.com/competitions/rsna-2024-lumbar-spine-degenerative-classification/overview
https://www.kaggle.com/competitions/mushroom-multiclass-classification/overview
https://www.kaggle.com/competitions/sofavision/overview
https://www.kaggle.com/competitions/super-resolution-in-video-games/overview
https://www.kaggle.com/competitions/mlnomads-mlolympiad24/overview
https://www.kaggle.com/competitions/sarfish-maritime-object-detection/overview
Team | Project | Time Slot |
---|
https://www.kaggle.com/competitions/beyond-visible-spectrum-ai-for-agriculture-2024/overview
https://www.kaggle.com/competitions/asl-signs