From 1ee77091c373b19d769bb29ac622294dbf22c240 Mon Sep 17 00:00:00 2001
From: Katrin Leinweber <9948149+katrinleinweber@users.noreply.github.com>
Date: Sat, 29 Feb 2020 13:45:39 +0100
Subject: [PATCH] Hyperlink DOI to preferred resolver

---
 01_intro.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/01_intro.ipynb b/01_intro.ipynb
index 17ca47f..44f1b4a 100644
--- a/01_intro.ipynb
+++ b/01_intro.ipynb
@@ -2252,7 +2252,7 @@
    "source": [
     "This model is using the *adult* dataset, from the paper [Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid](https://archive.ics.uci.edu/ml/datasets/adult), which contains some data regarding individuals (like their education, marital status, race, sex, etc.) and whether or not they have an annual income greater than \\$50k. The model is over 80\\% accurate, and took around 30 seconds to train.\n",
     "\n",
-    "Let's look at one more. Recommendation systems are very important, particularly in e-commerce. Companies like Amazon and Netflix try hard to recommend products or movies which you might like. Here's how to train a model which will predict which people might like which movie, based on their previous viewing habits, using the [MovieLens dataset](http://dx.doi.org/10.1145/2827872):"
+    "Let's look at one more. Recommendation systems are very important, particularly in e-commerce. Companies like Amazon and Netflix try hard to recommend products or movies which you might like. Here's how to train a model which will predict which people might like which movie, based on their previous viewing habits, using the [MovieLens dataset](https://doi.org/10.1145/2827872):"
    ]
   },
   {