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The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...
XOWA is a free, open-source application that helps download Wikipedia to a computer. Access all of Wikipedia offline, without an internet connection! Access all of Wikipedia offline, without an internet connection!
The dataset is labeled with semantic labels for 32 semantic classes. over 700 images Images Object recognition and classification 2008 [56] [57] [58] Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla RailSem19 RailSem19 is a dataset for understanding scenes for vision systems on railways. The dataset is labeled semanticly and ...
The iris data set is widely used as a beginner's dataset for machine learning purposes. The dataset is included in R base and Python in the machine learning library scikit-learn, so that users can access it without having to find a source for it. Several versions of the dataset have been published. [8]
LabelMe is a project created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) that provides a dataset of digital images with annotations. The dataset is dynamic, free to use, and open to public contribution. The most applicable use of LabelMe is in computer vision research. As of October 31, 2010, LabelMe has 187,240 ...
Extended MNIST (EMNIST) is a newer dataset developed and released by NIST to be the (final) successor to MNIST. [ 15 ] [ 16 ] MNIST included images only of handwritten digits. EMNIST includes all the images from NIST Special Database 19 (SD 19), which is a large database of 814,255 handwritten uppercase and lower case letters and digits.
Mnemosyne is written in Python, which allows its use on Microsoft Windows, Linux, and Mac OS X. A client program for review on Android devices is also available but needs to be synchronized by the desktop program. Users of the software usually make their own database of cards, although pre-made Mnemosyne databases are available, and it is ...
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]