MNIST Dataset

Welcome to the GitHub page of DeepTrackAI's MNIST dataset. The MNIST dataset is a large collection of handwritten digits and is widely used for training and evaluating machine learning and deep learning models.

Description

The MNIST dataset contains 60,000 training images and 10,000 testing images. Each image is a grayscale picture of a digit, and the associated label is the digit value (from 0 to 9).

• Dataset Size: 70,000 images
• Image Size: 28x28 pixels
• Color: Grayscale
• Labels: 10 (0 through 9)

Usage

To use the MNIST dataset in your project:

1. Clone this repository to your local machine.
2. Import the dataset into your machine learning framework of choice.
3. Train or evaluate your models using the dataset.

Download via Command Line

To clone the repository and access the MNIST dataset:

git clone -b mnist github.com/DeepTrackAI/MNIST_deeplay
cd MNIST_deeplay

Download Programmatically in Python

If you want to load the dataset directly into a Python script or Jupyter notebook:

import requests
from io import BytesIO
from zipfile import ZipFile

# URL to the repository (modify this if the dataset is hosted in a specific location or file)
DATASET_URL = 'https://github.com/DeepTrackAI/MNIST_dataset/raw/main/mnist.zip'

response = requests.get(DATASET_URL)
with ZipFile(BytesIO(response.content)) as z:
    z.extractall()

# Now you can load the dataset using your preferred library, e.g., deeplay, PyTorch, TensorFlow.

Acknowledgements

• The MNIST dataset was originally created by Yann LeCun, Corinna Cortes, and Christopher Burges. Their efforts have made it one of the benchmark datasets in the machine learning community.
• Official MNIST Database Website

License

The MNIST dataset is made available under the terms of the Creative Commons Attribution-Share Alike 3.0 license.

Contributing

If you find any issues with the dataset or have suggestions for improvements, please open an issue or submit a pull request.