90 datasets found
  1. h

    Data from: comps

    • huggingface.co
    Updated Apr 6, 2023
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    Kanishka Misra (2023). comps [Dataset]. https://huggingface.co/datasets/kanishka/comps
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 6, 2023
    Authors
    Kanishka Misra
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    COMPS is a dataset of minimal pair sentences in English that enables the testing knowledge of concepts and their properties in language models (LMs). Specifically, it tests the ability of LMs to attribute properties to everyday concepts, and demonstrate reasoning compatible with property inheritance, where subordinate concepts inherit the properties of their superordinate (hypernyms).

  2. R

    Data from: Comps Dataset

    • universe.roboflow.com
    zip
    Updated Feb 10, 2025
    + more versions
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    comps (2025). Comps Dataset [Dataset]. https://universe.roboflow.com/comps/comps-xh4dx
    Explore at:
    zipAvailable download formats
    Dataset updated
    Feb 10, 2025
    Dataset authored and provided by
    comps
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Components Bounding Boxes
    Description

    Comps

    ## Overview
    
    Comps is a dataset for object detection tasks - it contains Components annotations for 1,242 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  3. R

    Comp 26: Sign Detection Dataset

    • universe.roboflow.com
    zip
    Updated Oct 27, 2025
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    Cornell AutoBoat (2025). Comp 26: Sign Detection Dataset [Dataset]. https://universe.roboflow.com/cornell-autoboat-fz9yv/comp-26-sign-detection-qkjdf
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 27, 2025
    Dataset authored and provided by
    Cornell AutoBoat
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Buoys Targets 83UC Yx7E Bounding Boxes
    Description

    COMP 26: Sign Detection

    ## Overview
    
    COMP 26: Sign Detection is a dataset for object detection tasks - it contains Buoys Targets 83UC Yx7E annotations for 356 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  4. Healthcare Competitions Dataset

    • kaggle.com
    zip
    Updated Jul 19, 2025
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    Gouri Prakash (2025). Healthcare Competitions Dataset [Dataset]. https://www.kaggle.com/datasets/gouriprakash/healthcare-competitions
    Explore at:
    zip(2306357 bytes)Available download formats
    Dataset updated
    Jul 19, 2025
    Authors
    Gouri Prakash
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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

  5. h

    comp-serp-data

    • huggingface.co
    Updated Oct 26, 2025
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    Goker Cebeci (2025). comp-serp-data [Dataset]. https://huggingface.co/datasets/goker/comp-serp-data
    Explore at:
    Dataset updated
    Oct 26, 2025
    Authors
    Goker Cebeci
    Description

    Comprehensive SERP Data

    This dataset contains comprehensive search engine ranking data collected from Google and Bing, along with extracted technical and content features for analyzing search engine ranking algorithms.

      📊 Dataset Overview
    

    Total Records: 14,465 search results Search Engines: Google (5,895 results) and Bing (8,570 results) Keywords: 500 diverse search queries Features: 20 features including technical scores, content analysis, and ranking metadata… See the full description on the dataset page: https://huggingface.co/datasets/goker/comp-serp-data.

  6. R

    Comp Gate Seg Dataset

    • universe.roboflow.com
    zip
    Updated Oct 26, 2024
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    ADR Gate Detection (2024). Comp Gate Seg Dataset [Dataset]. https://universe.roboflow.com/adr-gate-detection/comp-gate-seg
    Explore at:
    zipAvailable download formats
    Dataset updated
    Oct 26, 2024
    Dataset authored and provided by
    ADR Gate Detection
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Gate Polygons
    Description

    Comp Gate Seg

    ## Overview
    
    Comp Gate Seg is a dataset for instance segmentation tasks - it contains Gate annotations for 1,275 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  7. G

    STEM Competitions Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 29, 2025
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    Growth Market Reports (2025). STEM Competitions Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/stem-competitions-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Aug 29, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    STEM Competitions Market Outlook



    According to our latest research, the global STEM competitions market size reached USD 1.71 billion in 2024, reflecting a robust landscape shaped by increasing investments in educational enrichment and workforce development. The market is projected to expand at a CAGR of 10.2% from 2025 to 2033, driven by the rising emphasis on science, technology, engineering, and mathematics (STEM) education worldwide. By 2033, the STEM competitions market is forecasted to reach USD 4.07 billion. The acceleration in demand for STEM talent, coupled with the growing integration of digital learning platforms and enhanced educational outreach, continues to be a major growth factor fueling the marketÂ’s expansion.




    One of the primary growth drivers for the STEM competitions market is the global push toward digital transformation and technological innovation. Governments, educational institutions, and private organizations are increasingly recognizing the critical importance of STEM skills for future economic development and competitiveness. As a result, there has been a significant increase in funding and resources allocated to STEM education, with competitions serving as a key strategy to engage students and nurture their interest in these fields. The proliferation of coding camps, robotics tournaments, and interdisciplinary science fairs further exemplifies the sectorÂ’s dynamic growth. These competitions not only foster creativity and problem-solving skills but also help bridge the gap between classroom learning and real-world applications, making STEM education more accessible and engaging for students of all ages.




    Another significant factor propelling the growth of the STEM competitions market is the advent of online and hybrid competition formats. The COVID-19 pandemic accelerated the adoption of digital learning and remote participation, making STEM competitions more inclusive and accessible to students around the globe. Online platforms have enabled students from remote and underserved regions to participate in prestigious competitions, democratizing access to high-quality STEM experiences. This shift toward digital engagement has also allowed organizers to reach a broader audience, reduce logistical barriers, and leverage data analytics to personalize learning experiences. As technology continues to evolve, the integration of virtual reality, artificial intelligence, and gamified learning modules is expected to further enhance the appeal and effectiveness of STEM competitions, thereby driving sustained market growth.




    Corporate partnerships and industry sponsorships represent another vital growth lever for the STEM competitions market. Leading technology companies, engineering firms, and scientific organizations are increasingly investing in STEM competitions as part of their talent pipeline development and corporate social responsibility initiatives. These partnerships often bring additional resources, mentorship opportunities, and exposure to cutting-edge technologies, enriching the overall competition experience. Furthermore, the growing trend of multidisciplinary competitions that blend robotics, coding, and engineering with entrepreneurship and design thinking is expanding the marketÂ’s scope and attracting a diverse range of participants. As the demand for STEM professionals continues to outpace supply, such initiatives are expected to play an increasingly central role in shaping the future workforce.



    In recent years, the concept of a Robotics Esports Competition League has gained traction, reflecting the merging of competitive gaming with robotics. This innovative approach leverages the excitement of esports to engage students in robotics, offering a dynamic platform where coding, engineering, and strategic thinking converge. Such leagues provide students with the opportunity to showcase their skills in a competitive yet collaborative environment, fostering a sense of community and shared learning. The integration of esports elements into robotics competitions not only enhances student engagement but also prepares them for future careers in technology-driven fields. As these leagues continue to evolve, they are expected to play a significant role in expanding the reach and appeal of STEM education, particularly among tech-savvy youth.




    From a regional perspective, North Ame

  8. Competitions participated in by horse owners and managers in the U.S....

    • statista.com
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    Statista, Competitions participated in by horse owners and managers in the U.S. 2010-2012 [Dataset]. https://www.statista.com/statistics/392362/number-of-competitions-participated-in-by-horse-owners-and-managers-us/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 5, 2012 - May 20, 2012
    Area covered
    United States
    Description

    This statistic shows the average number of competitions participated in by horse owners and managers in the United States in 2010 and 2012. In 2012, horse owners and managers participated in an average of **** competitions.

  9. R

    Workers’ Comp Triage Nurse Services Market Research Report 2033

    • researchintelo.com
    csv, pdf, pptx
    Updated Oct 1, 2025
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    Research Intelo (2025). Workers’ Comp Triage Nurse Services Market Research Report 2033 [Dataset]. https://researchintelo.com/report/workers-comp-triage-nurse-services-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Research Intelo
    License

    https://researchintelo.com/privacy-and-policyhttps://researchintelo.com/privacy-and-policy

    Time period covered
    2024 - 2033
    Area covered
    Global
    Description

    Workers’ Comp Triage Nurse Services Market Outlook



    According to our latest research, the Global Workers’ Comp Triage Nurse Services market size was valued at $2.1 billion in 2024 and is projected to reach $4.3 billion by 2033, expanding at a robust CAGR of 8.2% during the forecast period of 2024–2033. The primary driver behind this impressive growth is the increasing emphasis on workplace safety, efficient claims management, and the rising demand for cost-effective healthcare solutions for injured workers. As organizations and insurers seek to streamline the injury reporting and care process, the adoption of triage nurse services has become a critical component in reducing unnecessary emergency room visits, expediting care, and improving overall outcomes for both employees and employers.



    Regional Outlook



    North America holds the largest share of the Workers’ Comp Triage Nurse Services market, accounting for over 45% of the global revenue in 2024. This dominance is primarily attributed to the region’s mature workers' compensation infrastructure, stringent regulatory landscape, and high awareness of occupational health and safety protocols. The United States, in particular, benefits from a well-established insurance ecosystem and a culture of proactive injury management, enabling rapid adoption of telephonic and virtual triage solutions. Furthermore, the presence of leading service providers and advanced digital health technologies has fostered a competitive environment, allowing for continuous service innovation and enhanced patient outcomes. The integration of electronic health records and seamless communication between employers, insurers, and healthcare providers further accelerates the market’s growth in this region.



    The Asia Pacific region is projected to be the fastest-growing market, with a CAGR exceeding 10% through 2033. This rapid expansion is driven by increasing industrialization, rising workplace injury rates, and growing investments in digital health infrastructure. Countries such as China, India, and Australia are witnessing heightened employer awareness regarding workplace safety and compensation obligations. Additionally, the proliferation of mobile health platforms and improved internet penetration are making telephonic and virtual triage services more accessible in remote and underserved areas. Governments across the region are also introducing reforms to strengthen workers’ compensation frameworks, thereby creating a conducive environment for the adoption of triage nurse services. The influx of international service providers and strategic partnerships with local insurers further fuel market growth.



    Emerging economies in Latin America, the Middle East, and Africa are gradually embracing workers’ comp triage nurse services, albeit at a slower pace due to infrastructural and regulatory challenges. In these regions, the adoption is often hindered by limited access to digital health technologies, lack of standardized compensation policies, and varying levels of employer awareness. However, localized demand is rising as multinational corporations expand their operations and prioritize employee well-being. Policy reforms aimed at improving workplace safety and the entry of global service providers are expected to gradually overcome these barriers. Tailored solutions that address language, cultural, and regulatory nuances are essential for unlocking the full potential of these emerging markets.



    Report Scope






    Attributes Details
    Report Title Workers’ Comp Triage Nurse Services Market Research Report 2033
    By Service Type Telephonic Triage, Onsite Triage, Virtual Triage
    By End-User Insurance Companies, Employers, Third-Party Administrators, Healthcare Providers, Others
    By Application Injury Assessment, Case Management, Claims Management, Others

  10. h

    COMP-5112

    • huggingface.co
    Updated Oct 29, 2025
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    Nguyen Minh (2025). COMP-5112 [Dataset]. https://huggingface.co/datasets/nguyenminh4099/COMP-5112
    Explore at:
    Dataset updated
    Oct 29, 2025
    Authors
    Nguyen Minh
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    nguyenminh4099/COMP-5112 dataset hosted on Hugging Face and contributed by the HF Datasets community

  11. N

    Comp Prog Analyst, Comp Assoc - Software & Tech Support

    • data.cityofnewyork.us
    csv, xlsx, xml
    Updated Dec 2, 2025
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    Department of Citywide Administrative Services (DCAS) (2025). Comp Prog Analyst, Comp Assoc - Software & Tech Support [Dataset]. https://data.cityofnewyork.us/City-Government/Comp-Prog-Analyst-Comp-Assoc-Software-Tech-Support/c68r-hht5
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Dec 2, 2025
    Authors
    Department of Citywide Administrative Services (DCAS)
    Description

    A Civil Service List consists of all candidates who passed an exam, ranked in score order. An established list is considered active for no less than one year and no more than four years from the date of establishment. For more information visit DCAS’ “Work for the City” webpage at: http://www.nyc.gov/html/dcas/html/work/work.shtml

  12. COMP 4211 PA2

    • kaggle.com
    zip
    Updated Mar 7, 2024
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    Perry Lucas (2024). COMP 4211 PA2 [Dataset]. https://www.kaggle.com/datasets/perrylucas/comp-4211-pa1
    Explore at:
    zip(3235286207 bytes)Available download formats
    Dataset updated
    Mar 7, 2024
    Authors
    Perry Lucas
    Description

    Dataset

    This dataset was created by Perry Lucas

    Contents

    Dataset for COMP4211 PA2

  13. R

    Trash Ml Comp Dataset

    • universe.roboflow.com
    zip
    Updated Nov 23, 2025
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    USB (2025). Trash Ml Comp Dataset [Dataset]. https://universe.roboflow.com/usb-omtca/trash-ml-comp-2mwm3
    Explore at:
    zipAvailable download formats
    Dataset updated
    Nov 23, 2025
    Dataset authored and provided by
    USB
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Variables measured
    Trash Bounding Boxes
    Description

    Trash ML Comp

    ## Overview
    
    Trash ML Comp is a dataset for object detection tasks - it contains Trash annotations for 2,626 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  14. COMP-USD Stock Market @Kraken

    • kaggle.com
    zip
    Updated Mar 9, 2022
    + more versions
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    olmatz (2022). COMP-USD Stock Market @Kraken [Dataset]. https://www.kaggle.com/datasets/olmatz/compusd-stock-market-kraken
    Explore at:
    zip(8626548 bytes)Available download formats
    Dataset updated
    Mar 9, 2022
    Authors
    olmatz
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

    Content

    Data provided in this dataset are historical data from the beginning of COMP-USD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

    Trading history

    Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

    OHLCVT

    In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

    Don't hesitate to tell me if you need other period interval 😉 ...

    Update

    This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

    Inspiration

    Can you beat the market? Let see what you can do with these data!

  15. f

    Comp S.A. Financial Filings and Reports

    • financialreports.eu
    json, pdf
    Updated Oct 25, 2025
    + more versions
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    FinancialReports (2025). Comp S.A. Financial Filings and Reports [Dataset]. https://financialreports.eu/companies/comp/
    Explore at:
    json, pdfAvailable download formats
    Dataset updated
    Oct 25, 2025
    Dataset authored and provided by
    FinancialReports
    License

    https://financialreports.eu/terms/https://financialreports.eu/terms/

    Area covered
    Europe
    Description

    A dataset of public corporate filings (such as annual reports, quarterly reports, and ad-hoc disclosures) for Comp S.A. (CMP), provided by FinancialReports.eu.

  16. G

    Math Competitions Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Aug 22, 2025
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    Growth Market Reports (2025). Math Competitions Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/math-competitions-market
    Explore at:
    pptx, csv, pdfAvailable download formats
    Dataset updated
    Aug 22, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Math Competitions Market Outlook



    According to our latest research, the global math competitions market size reached USD 1.27 billion in 2024, demonstrating robust expansion driven by increasing emphasis on STEM education and talent identification. The market is expected to continue its upward trajectory, growing at a CAGR of 7.8% from 2025 to 2033, and is forecasted to reach USD 2.52 billion by 2033. This growth is fueled by rising awareness of the importance of mathematical skills in academic and professional success, as well as the proliferation of online platforms that make competitions more accessible worldwide.




    One of the primary growth factors for the math competitions market is the intensifying global focus on STEM (Science, Technology, Engineering, and Mathematics) education. Governments, educational institutions, and private organizations are increasingly investing in programs that nurture young mathematical talent, recognizing that proficiency in mathematics is foundational for innovation and economic competitiveness. The integration of math competitions into school curricula, as well as the endorsement by prominent educational boards, has significantly elevated the profile of these contests. As a result, participation rates have surged, with students and parents viewing math competitions as critical stepping stones for academic scholarships, university admissions, and future career opportunities.




    Technological advancements have also played a pivotal role in the expansion of the math competitions market. The digital transformation of education has enabled the emergence of online math competitions, which have democratized access for students in remote and underserved regions. These online platforms offer interactive problem-solving environments, real-time feedback, and global leaderboards, enhancing both the learning experience and the competitive spirit. The scalability and cost-effectiveness of online competitions have encouraged organizers to host events with larger participant pools, thereby driving market growth. Furthermore, the integration of artificial intelligence and data analytics into competition platforms has enabled personalized learning paths and performance tracking, further enhancing the value proposition for participants and sponsors alike.




    Another significant driver is the increasing involvement of private sector organizations and non-profits in sponsoring and organizing math competitions. These entities recognize the strategic importance of cultivating mathematical talent for future workforce needs, especially in fields such as data science, engineering, and finance. Corporate sponsorships, scholarships, and internship opportunities linked to math competitions have added substantial value, motivating higher participation and attracting top-tier talent. Additionally, the growing trend of professional math challenges and university-level competitions has expanded the market beyond the K-12 segment, catering to college students and working professionals seeking to benchmark their skills and gain recognition.




    From a regional perspective, Asia Pacific continues to dominate the math competitions market, accounting for the largest share in 2024. This leadership is attributed to the region’s strong cultural emphasis on academic excellence, particularly in mathematics, and government-led initiatives to promote STEM education. North America and Europe also represent significant markets, driven by established educational infrastructure, widespread adoption of digital learning tools, and a high concentration of prestigious math competitions. Meanwhile, Latin America and the Middle East & Africa are witnessing accelerated growth, bolstered by improving educational access and increasing investment in talent development programs. The regional diversification of math competitions is expected to further stimulate global market expansion over the next decade.





    Competition Type Analysis



    The competition type segment within the math competitions market is highl

  17. a

    Comp Plan Gallery

    • crc-planning-hub-segrass.hub.arcgis.com
    • segrass-segrass.hub.arcgis.com
    Updated May 19, 2021
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    SEGRASS (2021). Comp Plan Gallery [Dataset]. https://crc-planning-hub-segrass.hub.arcgis.com/items/b047c3728c634ad994fca10c371566c4
    Explore at:
    Dataset updated
    May 19, 2021
    Dataset authored and provided by
    SEGRASS
    Description

    The CRC Comprehensive Plan Apps showcases an overview of the County and City's comp plan data such as future land use, existing land use, and character areas.

  18. pneumonia comp proc images

    • kaggle.com
    zip
    Updated Feb 22, 2023
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    vbookshelf (2023). pneumonia comp proc images [Dataset]. https://www.kaggle.com/vbookshelf/pneumonia-comp-proc-images
    Explore at:
    zip(10705458404 bytes)Available download formats
    Dataset updated
    Feb 22, 2023
    Authors
    vbookshelf
    Description

    Notes

    1- Comp: https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/overview 2- Image list: In the attached csv file, please filter the "data_source" column by "pneu_comp". 3- Images have been padded to square. Padding was applied to the right and bottom so that the bounding box coords are not affected.

  19. h

    COMP

    • huggingface.co
    Updated Oct 24, 2025
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    Sraghvi Anchaliya (2025). COMP [Dataset]. https://huggingface.co/datasets/Sraghvi/COMP
    Explore at:
    Dataset updated
    Oct 24, 2025
    Authors
    Sraghvi Anchaliya
    Description

    Sraghvi/COMP dataset hosted on Hugging Face and contributed by the HF Datasets community

  20. COMP-XBT Stock Market @Kraken

    • kaggle.com
    zip
    Updated Mar 9, 2022
    + more versions
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    olmatz (2022). COMP-XBT Stock Market @Kraken [Dataset]. https://www.kaggle.com/datasets/olmatz/compxbt-stock-market-kraken
    Explore at:
    zip(4608241 bytes)Available download formats
    Dataset updated
    Mar 9, 2022
    Authors
    olmatz
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

    Content

    Data provided in this dataset are historical data from the beginning of COMP-XBT pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

    Trading history

    Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

    OHLCVT

    In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

    Don't hesitate to tell me if you need other period interval 😉 ...

    Update

    This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

    Inspiration

    Can you beat the market? Let see what you can do with these data!

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
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Kanishka Misra (2023). comps [Dataset]. https://huggingface.co/datasets/kanishka/comps

Data from: comps

COMPS

kanishka/comps

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Dataset updated
Apr 6, 2023
Authors
Kanishka Misra
License

Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically

Description

COMPS is a dataset of minimal pair sentences in English that enables the testing knowledge of concepts and their properties in language models (LMs). Specifically, it tests the ability of LMs to attribute properties to everyday concepts, and demonstrate reasoning compatible with property inheritance, where subordinate concepts inherit the properties of their superordinate (hypernyms).

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