Published July 17, 2024
| Version v1
Dataset
Open
MNIST_train_test_set.hdf5
Authors/Creators
- 1. Research Centre for Intelligent Information Technologies (CETINIA-DSLAB)
Description
The MNIST_784 dataset is a widely used machine learning benchmark dataset. It consists of 60,000 training and 10,000 test grayscale images of handwritten digits ranging from 0 to 9, making it visually straightforward and easy to work with. Moreover, each image is 28x28 pixels in size, resulting in a total of 784 dimensions when flattened, allowing researchers to explore algorithms in the context of high-dimensional data.
Technical info
The original train and test images databases from https://yann.lecun.com/exdb/mnist/ have been pre-split into train (60,000 elements) and test (100 elements) sets and stored into a HDF5 file.
Files
Files
(376.9 MB)
| Name | Size | |
|---|---|---|
|
md5:c8625776dba2ce67070b10a3b11a016d
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376.9 MB | Download |
Additional details
Related works
- Is version of
- Dataset: https://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz (URL)
- Dataset: https://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz (URL)
References
- Y. LeCun, L. Bottou, Y. Bengio, P. Haffner. 1998. Gradient-based learning applied to document recognition