# 111-2 UTA DL APP HW1 - Extended MNIST — Data

来源：https://www.kaggle.com/competitions/111-2-uta-dl-app-hw1/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

<h2> Data Format </h2>
The training and testing images are 28x28 gray images.  There are 62 classes (0 ~ 9 & A ~ Z & a ~z) in EMNIST dataset, which are labeled sequentially as 0, 1, 2, ..., 61. The original data are saved in both binary and MATLAB format. We've converted it into NumPy format so you can easily load the data.

<h3>👀 <b><i>Note! the data have been uploaded to Kaggle, which is called "NTUTEMNIST". </i></b></h3>
[www.kaggle.com/darkfanxing/ntutemnist](https://www.kaggle.com/darkfanxing/ntutemnist)
<h3><b><i>You can add the data directly in Python notebook. Our example code already included the data.</i></b></h3>
 [how to add dataset to your notebook.](https://ibb.co/HdNsLjq)

<h2>File descriptions</h2>
<ul>
<li><strong>emnist-byclass-train.npz</strong> - the training images and labels</li>
<li><strong>emnist-byclass-test.npz</strong> - the test images</li>
<li><strong>simple_nn_train.ipynb</strong> - A Jupyter notebook example of training a simple DNN model </li>
</ul>