What are the different datasets in machine learning?
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List of datasets for machine learning research
These datasets are used for machine-learningresearch and have been cited in peer-reviewedacademic journals. Datasets are an integral part of the field of machine learning. 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 produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce.
Image data
Text data
Sound data
Signal data
Physical data
Biological data
Anomaly data
question answer data
These datasets are used for machine-learningresearch and have been cited in peer-reviewedacademic journals. Datasets are an integral part of the field of machine learning. 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 produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce.
Image data
Text data
Sound data
Signal data
Physical data
Biological data
Anomaly data
question answer data
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During an AI development, we always rely on data. From training, tuning, model selection to testing, we use three different data sets: the training set, the validation set ,and the testing set. For your information, validation sets are used to select and tune the final ML model.
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