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Each file represents a single experiment and contains a single anomaly. The dataset represents a multivariate time series collected from the sensors installed on the testbed. There are two markups for Outlier detection (point anomalies) and Changepoint detection (collective anomalies) problems 30+ files (v0.9) CSV Anomaly detection
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.
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research.
The Fashion MNIST dataset is a large freely available database of fashion images that is commonly used for training and testing various machine learning systems. [1] [2] Fashion-MNIST was intended to serve as a replacement for the original MNIST database for benchmarking machine learning algorithms, as it shares the same image size, data format and the structure of training and testing splits.
Observations are profiles distributed on measured levels (pressure or depth) and organized by dates of measurement and type of platform. Main users of CORA dataset are ocean modelers who needs to constraint and initialize their model. CORA [1] is free of access and can be download via CORIOLIS website [2] in netCDF file format.
Data Commons places more emphasis on statistical data than is common for linked data and knowledge graph initiatives. It includes geographical, demographic, weather and real estate data alongside other categories, [3] describing states, Congressional districts, and cities in the United States as well as biological specimens, power plants, and elements of the human genome via the Encyclopedia ...
Caltech 101 is a data set of digital images created in September 2003 and compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro Perona at the California Institute of Technology.