Commit 639cbdfa authored by Luca Massimiliano Ghiringhelli's avatar Luca Massimiliano Ghiringhelli
Browse files

Update metainfo.json

parent f6bfa201
......@@ -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"
],
......
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