Loading...
Loading...
Student performance, MOOC logs, knowledge tracing, standardized tests, learning analytics
13,984 datasets
MNIST-derived digit samples converted into 840-token text sequences using a 64-character quantization scheme. Each entry includes dual 'up' and 'down' versions of the digit to facilitate rotation-invariant feature learning in Transformer-VAE models.
From 2005-06-16 to 2020-12-31, automated sensors at Santa Monica Pier collected oceanographic and surface meteorological data. The Institute of the Environment at UCLA collected the data, which was assembled by the Southern California Coastal Ocean Observing System (SCCOOS) and submitted to NOAA NCEI. Measurements include chlorophyll-a concentration, conductivity, salinity, water temperature, and hydrostatic pressure.
Automated sensors attached to Stearns Wharf collected measurements of chlorophyll a concentration, conductivity, salinity, water temperature, and hydrostatic pressure at frequent intervals from 2005 to 2020. The Marine Science Institute at UC Santa Barbara collected the data, which was assembled by the Southern California Coastal Ocean Observing System and submitted to NOAA NCEI. These data can provide local and regional information on mixing and upwelling, land run-off, and algal blooms.
Field observations of snow instabilities contains 589 snow profile observations with rutschblock tests, signs of instability, and avalanche danger assessments. The data were recorded primarily in the Davos region of the eastern Swiss Alps across the winter seasons from 2001-2002 to 2018-2019. Analysis and publication of this dataset was led by researchers including J. Schweizer.
The Municipal Institution "Poltava Children's and Youth Sports School Ü 1" reported on its activities in 2021. The dataset is an Excel file published on the eu_open_data platform by the States site of Ukraine. It likely contains quantitative and qualitative information about the school's operations.
A series of tutorials and code examples for the PaddlePaddle Fluid deep learning framework, organized as a CSDN blog column. The content covers model development and implementation patterns specific to the Fluid API architecture.
2005-06-16 to 2020-12-31 data from an automated shore station on Newport Pier, California. The dataset contains frequent interval measurements of chlorophyll concentration, conductivity, salinity, water temperature, and other oceanographic parameters. University of California, Irvine collected the data, which was assembled by the Southern California Coastal Ocean Observing System (SCCOOS) and submitted to NOAA's NCEI.
This repository provides datasets and source code specifically curated for the Visvesvaraya Technological University (VTU) 7th-semester 2018 Machine Learning Lab curriculum. Developed by rajathv and last updated in 2021, the collection supports the implementation of foundational algorithms including ID3, Naive Bayes, and Candidate Elimination.
Malyn city territorial community data on pedagogical workers in its educational institutions. The dataset likely contains information on educational levels, qualification categories, pedagogical titles, and work experience. It was published on the States site of Ukraine and last updated on 2021-02-17.
Appeals data for primary and secondary schools in Leeds, aggregated by academic year. The dataset is published by the Government Digital Service under an Open Government Licence and was last updated on November 12, 2020. It includes information on whether appeals were granted or refused based on infant class size legislation from the 2017/18 academic year onward.
A 2021 list details capital and current repairs for the Municipal Institution "Poltava Specialized Children's and Youth Sports School." The data originates from the States site of Ukraine and is available in .RTF and .XLSX formats. The specific scope, such as the number of repair projects or cost details, is not provided in the metadata.
Thousands of reCAPTCHA images comprise this machine learning collection published by AdityaJain1030 in 2021. The repository is a fork of @deathlyface's work and provides visual verification samples for computer vision tasks.
A list of preschool, secondary, and extracurricular educational institutions for the Dniprovskyi district in Ukraine. The data was published by the States site of Ukraine and last updated on November 24, 2020. The specific number of institutions and data fields are not detailed in the available metadata.
Linear entities like watercourses or unstable geological areas that represent the origin of flood risk for the PPR Vienna plan in Saint-Leonard-de-Noblat. The dataset was published by the French Geological Survey (BRGM) and last updated in November 2020. It characterizes real-world entities whose presence defines potential risk areas for flood prevention planning.
The Statute of Poltava Children's Art School is a document published on the eu_open_data platform. The dataset likely contains the official charter or governing rules for the institution. It was last updated on December 21, 2020.
A directory document for the Poltava Children's Art School, published on the eu_open_data platform. The document was last updated on 2020-12-17 13:02:21.849964 and originates from the States site of Ukraine. The specific content and structure of the directory are unknown.
Ucimlr provides a collection of datasets from the UCI Machine Learning Repository specifically formatted for the R programming environment, authored by Tyler Littlefield. Last updated in January 2021, the repository serves as a programmatic bridge for R users to access standard machine learning benchmarks. It facilitates the loading of classic datasets without requiring manual downloads from the web interface.
Created by Richard Iannone in 2021, this R package provides the specific datasets and functions required to follow the 'Exploring Data with R' textbook. It functions as a curated repository of example data designed for pedagogical use in data science instruction.
A shapefile created for a Master's thesis in Geography at the University of New Mexico analyzes the proximity of the Continental Divide to the Continental Divide National Scenic Trail. The dataset was produced by the Earth Data Analysis Center and last updated in December 2020. It is available in multiple GIS and data formats including QGIS, JSON, KML, and CSV.
This Python library provides a programmatic interface for the Remo application, focusing on the management of computer vision images and annotations. It enables developers to interact with dataset assets and label metadata through a dedicated API for computer vision workflows.