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Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...
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.
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
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]
It was found that machine learning systems trained and validated on SD-3 suffered significant drops in performance on the test set. [12] The original dataset from MNIST contained 128x128 binary images. Each was size-normalized to fit in a 20x20 pixel box while preserving their aspect ratio, and anti-aliased to grayscale.
Datasets in machine learning (1 C, 12 P) S. Statistical data sets (18 C, 32 P) Pages in category "Datasets" The following 4 pages are in this category, out of 4 total.
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]
List of datasets for machine-learning research. ... On data sets with, for example, overlapping Gaussian distributions – a common use case in artificial data ...