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8 | 8 | "source": [
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9 | 9 | "# How to train and deploy Learning To Rank\n",
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10 | 10 | "\n",
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11 |
| - "TODO: udpate the link to elastic/elasticsearch-labs instead of my fork before merging.\n", |
12 |
| - "\n", |
13 |
| - "[](https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/ltr-notebook/notebooks/search/08-learning-to-rank.ipynb)\n", |
| 11 | + "[](https://colab.research.google.com/github/elastic/elasticsearch-labs/blob/main/notebooks/search/08-learning-to-rank.ipynb)\n", |
14 | 12 | "\n",
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15 | 13 | "In this notebook we will see an example on how to train a Learning To Rank model using [XGBoost](https://xgboost.ai/) and how to deploy it to be used as a rescorer in Elasticsearch.\n",
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16 | 14 | "\n",
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119 | 117 | "\n",
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120 | 118 | "In this example notebook we will use a dataset derived from [MSRD](https://github.com/metarank/msrd/tree/master) (Movie Search Ranking Dataset).\n",
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121 | 119 | "\n",
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122 |
| - "The dataset is available [here](https://github.com/elastic/elasticsearch-labs/tree/main/ltr-notebook/notebooks/search/sample_data/learning-to-rank/) and contains the following files:\n", |
| 120 | + "The dataset is available [here](https://github.com/elastic/elasticsearch-labs/tree/main/notebooks/search/sample_data/learning-to-rank/) and contains the following files:\n", |
123 | 121 | "\n",
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124 | 122 | "- **movies_corpus.jsonl.gz**: The movies dataset which will be indexed.\n",
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125 | 123 | "- **movies_judgements.tsv.gz**: A file containing relevance judgments for a set of queries.\n",
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136 | 134 | "source": [
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137 | 135 | "from urllib.parse import urljoin\n",
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138 | 136 | "\n",
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139 |
| - "DATASET_BASE_URL = \"https://raw.githubusercontent.com/elastic/elasticsearch-labs/ltr-notebook/notebooks/search/sample_data/learning-to-rank/\"\n", |
| 137 | + "DATASET_BASE_URL = \"https://raw.githubusercontent.com/elastic/elasticsearch-labs/main/notebooks/search/sample_data/learning-to-rank/\"\n", |
140 | 138 | "\n",
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141 | 139 | "CORPUS_URL = urljoin(DATASET_BASE_URL, \"movies-corpus.jsonl.gz\")\n",
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142 | 140 | "JUDGEMENTS_FILE_URL = urljoin(DATASET_BASE_URL, \"movies-judgments.tsv.gz\")\n",
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