This dataset contains the set of Kaggle competitions that are pertinent to healthcare. The dataset was created following the analysis of the Competitions.csv file which is available at https://www.kaggle.com/datasets/kaggle/meta-kaggle

Dataset

This dataset was created by Jørgen Sandhaug

Released under Apache 2.0

Contents

Compressed (.zip) archive containing the data set in .csv format and a README.txt file explaining the columns. (ZIP)

Dataset Card for [LLM Science Exam Kaggle Competition]

  Dataset Summary

https://www.kaggle.com/competitions/kaggle-llm-science-exam/data

  Languages

[en, de, tl, it, es, fr, pt, id, pl, ro, so, ca, da, sw, hu, no, nl, et, af, hr, lv, sl]

  Dataset Structure

Columns prompt - the text of the question being asked A - option A; if this option is correct, then answer will be A B - option B; if this option is correct, then answer will be B C - option C; if this… See the full description on the dataset page: https://huggingface.co/datasets/Sangeetha/Kaggle-LLM-Science-Exam.

Dataset

This dataset was created by Budi Ryan

Released under CC0: Public Domain

Contents

Dataset

This dataset was created by Mochammad Ariel Sulton

Contents

📝 Description:

A cleaned version of Competitions.csv focused on timeline analysis.

✅ Includes: CompetitionId, Title, Deadline, EnabledDate, HostSegmentTitle ✅ Helps understand growth over time, and regional hosting focus ✅ Can be joined with teams_clean.csv and user_achievements_clean.csv

This dataset was developed as part of a challenge to segment building footprints from aerial imagery. The goal of the challenge was to accelerate the development of more accurate, relevant, and usable open-source AI models to support mapping for disaster risk management in African cities [Read more about the challenge]. The data consists of drone imagery from 10 different cities and regions across Africa

This dataset contains crop types of agricultural fields in four states of Uttar Pradesh, Rajasthan, Odisha and Bihar in northern India. There are 13 different classes in the dataset including Fallow land and 12 crop types of Wheat, Mustard, Lentil, Green pea, Sugarcane, Garlic, Maize, Gram, Coriander, Potato, Bersem, and Rice. The dataset is split to train and test collections as part of the AgriFieldNet India Competition. Ground reference data for this dataset is collected by IDinsight’s Data on Demand team. Radiant Earth Foundation carried out the training dataset curation and publication. This training dataset is generated through a grant from the Enabling Crop Analytics at Scale (ECAAS) Initiative funded by The Bill & Melinda Gates Foundation and implemented by Tetra Tech.

Dataset

This dataset was created by Lisa Sharapova

Released under Apache 2.0

Contents

Context

For the exploration of Kaggle's public data on competitions.

Content

This file contains all the details of the Competitions Rankings on Kaggle. There are 8 features that correspond to a given rank. Data last scraped on 27-SEP-2018.

Acknowledgements

Thanks to Ashhad for his support in scraping the Kaggle Competitions rankings webpage.

Inspiration

Meta Kaggle

This data set is for creating predictive models for the CrunchDAO tournament. Registration is required in order to participate in the competition, and to be eligible to earn $CRUNCH tokens.

See notebooks (Code tab) for how to import and explore the data, and build predictive models.

• EDA
• QuickStarter

See Terms of Use for data license.

This dataset contains match score data from major international competitions across 12 team ball sports: basketball, cricket, field hockey, futsal, handball, ice hockey, lacrosse, roller hockey, rugby, soccer, volleyball, and water polo. The dataset was obtained by web scraping data available on Wikipedia pages and includes, for each sport, the following information related to individual matches: the year of the competition edition when a match occurred, the names of the two opposing teams, their respective scores, and the name of the winning team.

Dataset

This dataset was created by Satyam Kr

Released under MIT

Contents

This chipped training dataset is over Wa and includes high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in developing the ramp baseline model and contains 7,615 tiles and 68,072 individual buildings. The satellite imagery resolution is 32 cm and was sourced from Maxar ODP (1040010056B6FA00). Dataset keywords: Urban, Peri-urban

Dataset

This dataset was created by Muhammad Ahmed

Contents

Dataset

This dataset was created by Udvas Basak 2

Contents

atama cup #17 was held8/29-8/31 in Japanese data competition platform. (https://www.guruguru.science/competitions/24/leaderboard) These dataset are competition dataset!

Context

This dataset contains top 100 of Kaggle competitions ranking. The dataset will be updated every month.

Content

100 rows and 13 columns. Columns' description are listed below.

• User : Name of the user
• Tier : Grandmaster, Master or Expert
• Company/School : Company/School info of the user if mentioned
• Country : Country info of the user if mentioned
• Competitions_Num : Number of competitions joined
• Competitions_Gold : Number of competitions gold medals won
• Competitions_Silver : Number of competitions silver medals won
• Competitions_Bronze : Number of competitions bronze medals won
• Datasets_Num : Number of public datasets
• Notebooks_Num : Number of public notebooks
• Discussions_Num : Number of topics/comments posted
• Points : Total points
• Profile : Link of Kaggle profile

Acknowledgements

Data from Kaggle. Image from Smartcat.

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This dataset contains a collection of frequently asked questions (FAQ) collected from the Top 3 write-ups of text data competitions from 2021 to 2023. The aim of this dataset is to provide insights and future directions that the ML community can address in the short term.