Update metainfo.json

metainfo.json

@@ -3,31 +3,30 @@
     "Langer, Marcel F."
   ],
   "email": "langer@fhi-berlin.mpg.de",
-  "title": "Kernel Ridge Regression for Materials Property Prediction: A Tutorial Introduction",
-  "description": "In this tutorial, we'll explore the application of kernel ridge regression to the prediction of materials properties. We will begin with a largely informal, pragmatic introduction to kernel ridge regression, including a rudimentary implementation, in order to become familiar with the basic terminology and considerations. We will then discuss representations, and re-trace the NOMAD 2018 Kaggle challenge.",
+  "title": "Introduction to kernel ridge regression for materials-property prediction",
+  "description": "In this tutorial, we will explore the application of kernel ridge regression to the prediction of materials properties. We will begin with a largely informal, pragmatic introduction to kernel ridge regression, including a rudimentary implementation, in order to become familiar with the basic terminology and considerations. We will then discuss representations, and re-trace the NOMAD 2018 Kaggle challenge.",
   "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-krr4mat",
   "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/krr4mat.ipynb",
   "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/krr4mat.ipynb",
   "link_video": "https://www.youtube.com/watch?v=H_MVlljpYHw",
-  "updated": "2020-10-30",
+  "updated": "2020-12-15",
   "flags":{
     "featured": true,
     "top_of_list": false
   },
    "labels": {
-    "application_keyword": [
-      "Formation energy prediction"
-    ],
     "application_section": [
       "Tutorials for artificial-intelligence methods"
     ],
     "application_system": [
-      "Group-III oxides"
+      "Transparent conducting oxides"
     ],
     "category": [
       "beginner_tutorial"
     ],
-    "data_analytics_method": [
+    "ai_methods": [
+      "Supervised learning"
+      "Regression"
       "Kernel ridge regression",
       "SOAP"
     ],