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Covertype Dataset Data for predicting forest cover type strictly from cartographic variables. Many geographical features given. 581,012 Text Classification 1998 [310] [311] J. Blackard et al. Abscisic Acid Signaling Network Dataset Data for a plant signaling network. Goal is to determine set of rules that governs the network. None. 300 Text
RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
ParaView is an open-source, multi-platform data analysis and visualization application. ParaView is known and used in many different communities to analyze and visualize scientific data sets. [2] It can be used to build visualizations to analyze data using qualitative and quantitative techniques.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
The four datasets composing Anscombe's quartet. All four sets have identical statistical parameters, but the graphs show them to be considerably different. Anscombe's quartet comprises four datasets that have nearly identical simple descriptive statistics, yet have very different distributions and appear very different when graphed.
Data Commons is an open-source platform [1] created by Google [2] that provides an open knowledge graph, combining economic, scientific and other public datasets into a unified view. [3] Ramanathan V. Guha , a creator of web standards including RDF , [ 4 ] RSS , and Schema.org , [ 5 ] founded the project, [ 6 ] which is now led by Prem Ramaswami.
It supports the temporal, geospatial, topical, and network analysis and visualization of datasets at the micro (individual), meso (local), and macro (global) levels. Users of the tool can: Access science datasets online or load their own. Perform different types of analysis with the most effective algorithms available.
The r/dataisbeautiful subreddit requires users submitting visualizations to clearly credit both the individual who created the visualization and the source of the data on which it is based. If someone submits a visualization they created themselves, the rules require them to put "[OC]" in the title of the submission, and to identify the source ...