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10 Best Datasets for Deep Learning [2023]

Deep learning is one of the most exciting and rapidly growing fields in artificial intelligence, with applications in computer vision, natural language processing, speech recognition, and many other areas. The performance of deep learning algorithms is heavily dependent on the quality and size of the training data. In this article, we will be exploring the 10 best datasets for deep learning in 2023.

Dataset NameType of DataSizePopularityDownload LinkDescription
MNISTImages70,000 28×28 grayscale imagesVery Popularhttp://yann.lecun.com/exdb/mnist/The MNIST dataset is a set of 70,000 28×28 grayscale images of handwritten digits, used for training and testing machine learning algorithms.
CIFAR-10Images50,000 32×32 color training images and 10,000 32×32 color test imagesPopularhttps://www.cs.toronto.edu/~kriz/cifar.htmlThe CIFAR-10 dataset consists of 50,000 32×32 color training images and 10,000 32×32 color test images in 10 classes, including airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks.
ImageNetImagesOver 14 million imagesVery Popularhttp://image-net.org/ImageNet is a large-scale visual recognition dataset with over 14 million images in more than 20,000 categories.
MS COCOImages330,000 imagesPopularhttp://cocodataset.org/#homeThe MS COCO dataset is a large-scale image recognition, segmentation, and captioning dataset with 330,000 images.
Fashion MNISTImages70,000 28×28 grayscale imagesPopularhttps://github.com/zalandoresearch/fashion-mnistThe Fashion MNIST dataset is a set of 70,000 28×28 grayscale images of fashion items, including t-shirts, trousers, bags, and shoes, used for training and testing machine learning algorithms.
SVHNImages73,257 digit images for training and 26,032 digit images for testingPopularhttp://ufldl.stanford.edu/housenumbers/The Street View House Numbers (SVHN) dataset consists of 73,257 digit images for training and 26,032 digit images for testing, taken from Google Street View images.
PASCAL VOCImagesOver 20,000 imagesPopularhttp://host.robots.ox.ac.uk/pascal/VOC/The PASCAL Visual Object Classes (VOC) dataset is a standardized image dataset for object recognition and segmentation, containing over 20,000 images.
Caltech-101Images9,147 images of 101 object categoriesPopularhttp://www.vision.caltech.edu/Image_Datasets/Caltech101/The Caltech-101 dataset is a set of 9,147 images of 101 object categories, including animals, vehicles, and everyday objects.
STL-10Images5,000 32×32 color training images and 8,000 32×32 color test imagesPopularhttps://cs.stanford.edu/~acoates/stl10/The STL-10 dataset consists of 5,000 32×32 color training images and 8,000 32×32 color test images in 10 classes, including airplane, bird, car, cat, deer, dog, horse, monkey, ship, and truck.
VGGFace2Images3.31 million imagesPopularhttp://www.robots.ox.ac.uk/~vgg/data/vgg_face2/The VGGFace2 dataset is a large-scale face recognition dataset, containing 3.31 million images of faces from 9,131 subjects.
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