Loading...
Loading...
General ML benchmarks, tabular data, AutoML, recommendation systems, anomaly detection, evaluation suites
147,277 datasets
Qatar National Library provides a high-resolution digital master copy of manuscript HC.MS.03192 from its Heritage Collection. The 618.4 MB dataset, released under a CC0 1.0 license, contains a Quranic fragment written in Kufic script. The record was last updated on June 2, 2026, and links to the full catalog and digitized manuscript are included in the description.
Qatar National Library provides a high-resolution digital master copy of manuscript HC.MS.2017.0008. The dataset is a 40.0 MB ZIP file containing two pages of the Quran written in Kufic script. It was last updated on 2026-06-02 and is released under a CC0 1.0 license.
A high-resolution digital master copy of manuscript HC.MS.03098 from the Qatar National Library Heritage Collection. The 81.1 MB ZIP file provides access to digitized manuscript fragments. Qatar National Library published this dataset under a CC0 1.0 license, with a last recorded update in June 2026.
A high-resolution digital master copy of manuscript HC.MS.03122 from the Qatar National Library Heritage Collection. The dataset is a single 84.3 MB ZIP file containing the digitized manuscript, made available under a CC0 1.0 license. The record was last updated on June 2, 2026.
A high-resolution digital master copy of manuscript HC.MS.03099 from the Qatar National Library Heritage Collection. The dataset is a single 80.3 MB ZIP file, published by Qatar National Library under a CC0 1.0 license. The record was last updated on June 2, 2026.
Qatar National Library provides a high-resolution digital master copy of manuscript HC.MS.03100 from its Heritage Collection. The dataset is a single 82.7 MB ZIP file containing a Quranic manuscript fragment. It was last updated on 2026-06-02 and is released under a CC0 1.0 Public Domain Dedication license.
A high-resolution digital master copy of manuscript HC.MS.03095 from the Qatar National Library Heritage Collection. The dataset is a single 80.2 MB ZIP file published by Qatar National Library on figshare. The record was last updated on June 2, 2026.
Qatar National Library provides a high-resolution digital master copy of manuscript HC.MS.03096, a Quranic fragment. The 79.2 MB ZIP file is published under a CC0 1.0 license. The dataset was last updated on June 2, 2026.
A 93.0 MB high-resolution digital master copy of manuscript HC.MS.03145 from the Qatar National Library Heritage Collection. The dataset contains four folios from the Quran, digitized and shared under a CC0 1.0 license. It was last updated on June 2, 2026, by Qatar National Library.
A 94.6 MB high-resolution digital master copy of manuscript HC.MS.03146 from the Qatar National Library Heritage Collection. The dataset, published by Qatar National Library, contains four folios from a Quranic manuscript. The last update to the record was on 2026-06-02.
95.4 MB high-resolution digital master copy of manuscript HC.MS.03144 from the Qatar National Library Heritage Collection. The dataset is a ZIP file containing four folios of Quranic text, published under a CC0-1.0 license by Qatar National Library. The record was last updated on June 2, 2026.
Qatar National Library provides a high-resolution digital master copy of manuscript HC.MS.03123 from its Heritage Collection. The dataset is a 45.4 MB ZIP file containing images of Quranic manuscript fragments. It was last updated on 2026-06-02 and is published under a CC0 1.0 license.
A 94.2 MB high-resolution digital master copy of manuscript HC.MS.03143 from the Qatar National Library Heritage Collection. The dataset, titled 'Four Quranic Folios', was published by Qatar National Library and last updated on 2026-06 02. It is provided under a CC0-1.0 license.
Registration and enrollment records for businesses in Villavicencio, Colombia, whose reported economic activity corresponds to vehicle dealerships under CIIU codes G4511 and G4512. The data was registered by the Villavicencio Chamber of Commerce and published on the datos.gov.co platform. The dataset's last recorded update was on 2026-05-18.
Jia-Qi Ma published metabolomics data from 67 carotid artery plaque samples (40 stable, 27 unstable) on figshare in May 2026. The dataset contains results from a non-targeted metabolomics analysis identifying 98 differentially abundant metabolites. Four machine learning algorithms were used to construct feature analysis models and screen for potential metabolic biomarkers associated with unstable plaques.
A non-targeted metabolomics analysis of 67 carotid artery plaque samples (40 stable, 27 unstable) collected for a study published in 2026. The dataset contains metabolite signatures used to identify 98 differentially abundant metabolites and potential biomarkers for unstable plaques. It was created by Jia-Qi Ma and is shared under a CC-BY-4.0 license.
Jia-Qi Ma's dataset contains non-targeted metabolomics data from 67 carotid artery plaque samples (40 stable, 27 unstable). The study identified 98 metabolites differentially associated with unstable plaques and used four machine learning algorithms to screen for potential biomarkers. The dataset was last updated on 2026-05-12.
A non-targeted metabolomics analysis was performed on 67 carotid artery plaque samples (40 stable and 27 unstable). The study, authored by Jia-Qi Ma and last updated in May 2026, identified 98 metabolites differentially associated with unstable plaques and used four machine learning algorithms to screen for potential biomarkers.
A non-targeted metabolomics analysis of 67 carotid artery plaque samples (40 stable and 27 unstable) was performed to investigate metabolic changes. The study, authored by Jia-Qi Ma and last updated in May 2026, identified 98 metabolites differentially associated with unstable plaques and used four machine learning algorithms to screen for potential biomarkers.
Non-targeted metabolomics data from 67 carotid artery plaque samples, comprising 40 stable and 27 unstable cases. The dataset, created by Jia-Qi Ma and last updated in 2026, identifies 98 metabolites significantly associated with unstable plaques and uses four machine learning algorithms to screen for potential biomarkers. It includes results from KEGG enrichment analysis linking metabolites to specific signaling and metabolic pathways.