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OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research. These datasets consist primarily of images or videos for tasks such as object detection, facial recognition, and multi-label classification.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
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.
Pages in category "Datasets in machine learning" The following 12 pages are in this category, out of 12 total. ... Training, validation, and test data sets
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. [1] [2] The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. [3]
The NSynth dataset is composed of 305,979 one-shot instrumental notes featuring a unique pitch, timbre, and envelope, sampled from 1,006 instruments from commercial sample libraries. [8] For each instrument the dataset contains four-second 16 kHz audio snippets by ranging over every pitch of a standard MIDI piano, as well as five different ...
80 Million Tiny Images is a dataset intended for training machine learning systems constructed by Antonio Torralba, Rob Fergus, and William T. Freeman in a collaboration between MIT and New York University. It was published in 2008. The dataset has size 760 GB.