not-MNIST Dataset

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Visualization of the not-MNIST Dataset in the Deep Lake UI

not-MNIST Dataset

What is not-MNIST Dataset?

The not-MNIST dataset comprises of some freely accessible fonts and symbols extracted to create a dataset similar to MNIST. The dataset is divided into two parts: a relatively small hand-cleaned portion of approximately 19k samples and a larger uncleaned portion of 500k samples. There are ten classes, with letters A-J drawn from various fonts.

Download not-MNIST Dataset in Python

Instead of downloading the not-MNIST dataset in Python, you can effortlessly load it in Python via our Deep Lake open source with just one line of code.

Load not-MNIST-small Dataset in Python

				
					import deeplake
ds = deeplake.load('hub://activeloop/not-mnist-small')

Load not-MNIST-large Dataset in Python

				
					import deeplake
ds = deeplake.load('hub://activeloop/not-mnist-large')

not-MNIST Dataset Structure

not-MNIST Data Fields

image: tensor containing the 28×28 image.
label: tensor containing labels that represent letters from A to J.

How to use not-MNIST Dataset with PyTorch and TensorFlow in Python

Train a model on not-MNIST dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)

Train a model on the not-MNIST dataset with TensorFlow in Python

				
					dataloader = ds.tensorflow()

Additional Information about not-MNIST Dataset

not-MNIST Dataset Description

Homepage: https://yaroslavvb.blogspot.com/2011/09/notmnist-dataset.html

not-MNIST Dataset Curators

Yaroslav Bulatov

not-MNIST Dataset Licensing Information

Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license. If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

not-MNIST Dataset Citation Information

				
					@article{bulatov2011notmnist,
title={Notmnist dataset},
author={Bulatov, Yaroslav},
journal={Google (Books/OCR), Tech. Rep.[Online]. Available: http://yaroslavvb. blogspot. it/2011/09/notmnist-dataset. html},
volume={2},
year={2011}
}

not-MNIST Dataset FAQs

What is the not-MNIST dataset for Python?

The not-MNIST dataset is divided into two parts: a relatively small hand-cleaned portion of approximately 19k samples and a larger uncleaned portion of 500k samples.

How to download the not-MNIST dataset in Python?

You can load the not-MNIST dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load the not-MNIST dataset training subset and testing subset in Python.

How can I use the not-MNIST dataset in PyTorch or TensorFlow?

You can stream the not-MNIST dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to train a model on the not-MNIST dataset with PyTorch in Python or train a model on the not-MNIST dataset with TensorFlow in Python.