Update clustering tutorial for production

tutorials.json

@@ -85,45 +85,6 @@
         ]
       }
     },
-    {
-      "authors": [
-        "Leitherer, Andreas",
-        "Sbail\u00f2, Luigi",
-        "Ghiringhelli, Luca M."
-      ],
-      "email": "leitherer@fhi-berlin.mpg.de",
-      "title": "Hands-on tutorial: Regression using multilayer perceptrons",
-      "description": "In this tutorial we will use the ElemNet neural network architecture (https://github.com/NU-CUCIS/ElemNet) to predict the volume per atom of inorganic compounds, where the open quantum materials database (OQMD) is used as a resource (specifically, the data is taken from Ward et. al., npj Comput. Mater. 2, 16028 (2016)).",
-      "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-tutorial-template",
-      "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/{tutorial}.ipynb",
-      "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/{tutorial}.ipynb",
-      "updated": "2020-04-09",
-      "flags": {
-        "featured": true,
-        "top_of_list": false
-      },
-      "labels": {
-        "application_keyword": [
-          "Neural networks / deep learning",
-          "Descriptors"
-        ],
-        "application_section": [
-          "Materials property prediction"
-        ],
-        "application_system": [
-          "Inorganic compounds taken from the OQMD database"
-        ],
-        "category": [
-          "Tutorial"
-        ],
-        "data_analytics_method": [
-          "Neural networks"
-        ],
-        "platform": [
-          "jupyter"
-        ]
-      }
-    },
     {
       "authors": [
         "Bieniek, Bj\u00f6rn",
@@ -207,8 +168,8 @@
         "Ghiringhelli, Luca M."
       ],
       "email": "sbailo@fhi-berlin.mpg.de",
-      "title": "Introduction into clustering",
-      "description": "In this tutorial we introduce into the most popular clustering algorithms",
+      "title": "Introduction to clustering",
+      "description": "In this tutorial we introduce to the most popular clustering algorithms. We focus on partitioning, hierarchical and density-based clustering algorithms, and methods are tested on artificial datasets of increasing complexity",
       "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-clustering-tutorial",
       "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/clustering_tutorial.ipynb",
       "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/clustering_tutorial.ipynb",
@@ -266,7 +227,7 @@
           "Tutorials for artificial-intelligence methods"
         ],
         "application_system": [
-          "Images"
+          "Imates"
         ],
         "category": [
           "Tutorial"
@@ -364,46 +325,6 @@
         ]
       }
     },
-    {
-      "authors": [
-        "Lucas Foppa",
-        "Thomas Purcell",
-        "Sbail\u00f2, Luigi",
-        "Christopher Bartel",
-        "Ghiringhelli, Luca M."
-      ],
-      "email": "ghiringhelli@fhi-berlin.mpg.de",
-      "title": "Finding a tolerance factor to predict perovskite stability with SISSO",
-      "description": "In this tutorial...",
-      "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-perovskite-tolerance-factor",
-      "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/{tutorial}.ipynb",
-      "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/{tutorial}.ipynb",
-      "updated": "2020-04-09",
-      "flags": {
-        "featured": true,
-        "top_of_list": false
-      },
-      "labels": {
-        "application_keyword": [
-          "SISSO"
-        ],
-        "application_section": [
-          "Materials property prediction"
-        ],
-        "application_system": [
-          "Perovskite"
-        ],
-        "category": [
-          "Tutorial"
-        ],
-        "data_analytics_method": [
-          "SISSO"
-        ],
-        "platform": [
-          "jupyter"
-        ]
-      }
-    },
     {
       "authors": [
         "Langer, Marcel F."
@@ -524,43 +445,6 @@
         ]
       }
     },
-    {
-      "authors": [
-        "Sbail\u00f2, Luigi",
-        "Ghiringhelli, Luca M."
-      ],
-      "email": "ghiringhelli@fhi-berlin.mpg.de",
-      "title": "...",
-      "description": "...",
-      "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-hisisso-perovskites",
-      "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/hisisso_perovskites.ipynb",
-      "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/hisisso_perovskites.ipynb",
-      "updated": "2020-09-5",
-      "flags": {
-        "featured": true,
-        "top_of_list": false
-      },
-      "labels": {
-        "application_keyword": [
-          "..."
-        ],
-        "application_section": [
-          "..."
-        ],
-        "application_system": [
-          "..."
-        ],
-        "category": [
-          "..."
-        ],
-        "data_analytics_method": [
-          "..."
-        ],
-        "platform": [
-          "jupyter"
-        ]
-      }
-    },
     {
       "authors": [
         "Liu, Xiangyue",

analytics-clustering-tutorial @ 1b386428

-Subproject commit 9a2365d74049bb80514e5c82bc3507035d6e779d
+Subproject commit 1b3864285d6a7d6d0e04754692622ca6f83fffbe