From 1e13975736d3c303293d44952c94ade6f525b97e Mon Sep 17 00:00:00 2001 From: "Christine P. Chai" <star1327p@gmail.com> Date: Sun, 9 Feb 2025 12:01:13 -0800 Subject: [PATCH] DOC: Update the MNIST data link --- content/tutorial-deep-learning-on-mnist.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/tutorial-deep-learning-on-mnist.md b/content/tutorial-deep-learning-on-mnist.md index fc874f02..89647016 100644 --- a/content/tutorial-deep-learning-on-mnist.md +++ b/content/tutorial-deep-learning-on-mnist.md @@ -62,7 +62,7 @@ This tutorial can be run locally in an isolated environment, such as [Virtualenv ## 1. Load the MNIST dataset -In this section, you will download the zipped MNIST dataset files originally stored in [Yann LeCun's website](http://yann.lecun.com/exdb/mnist/). Then, you will transform them into 4 files of NumPy array type using built-in Python modules. Finally, you will split the arrays into training and test sets. +In this section, you will download the zipped MNIST dataset files originally developed by Yann LeCun's research team. (More details of the MNIST dataset are available on [Kaggle](https://www.kaggle.com/datasets/hojjatk/mnist-dataset).) Then, you will transform them into 4 files of NumPy array type using built-in Python modules. Finally, you will split the arrays into training and test sets. **1.** Define a variable to store the training/test image/label names of the MNIST dataset in a list: