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Update clustering_with_embeddings.ipynb #393

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Apr 30, 2024
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Update clustering_with_embeddings.ipynb #393

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Update clustering_with_embeddings.ipynb
JosBecker Apr 30, 2024
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Use up-to-date URLs
markmcd Apr 30, 2024
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6 changes: 3 additions & 3 deletions site/en/gemini-api/tutorials/clustering_with_embeddings.ipynb
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"\n",
"This tutorial demonstrates how to visualize and perform clustering with the embeddings from the Gemini API. You will visualize a subset of the 20 Newsgroup dataset using [t-SNE](https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html){:.external} and cluster that subset using the KMeans algorithm.\n",
"\n",
"For more information on getting started with embeddings generated from the Gemini API, check out the [Python quickstart](../tutorials/python_quickstart.ipynb#use_embeddings).\n",
"For more information on getting started with embeddings generated from the Gemini API, check out the [Python quickstart](https://ai.google.dev/tutorials/python_quickstart#use_embeddings).\n",
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"\n",
"## Prerequisites\n",
"\n",
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"source": [
"Key Point: Next, you will choose a model. Any embedding model will work for this tutorial, but for real applications it's important to choose a specific model and stick with it. The outputs of different models are not compatible with each other.\n",
"\n",
"**Note**: At this time, the Gemini API is [only available in certain regions](https://developers.generativeai.google/available_regions)."
"**Note**: At this time, the Gemini API is [only available in certain regions](https://ai.google.dev/available_regions)."
]
},
{
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"\n",
"There are other clustering algorithms outside of KMeans as well, such as [density-based spatial clustering (DBSCAN)](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html){:.external}.\n",
"\n",
"To learn how to use other services in the Gemini API, visit the [Python quickstart](../tutorials/python_quickstart.ipynb). To learn more about how you can use the embeddings, check out the [examples](../examples?keywords=embed) available. To learn how to create them from scratch, see TensorFlow's [Word Embeddings](https://www.tensorflow.org/text/guide/word_embeddings){:.external} tutorial."
"To learn how to use other services in the Gemini API, visit the [Python quickstart](https://ai.google.dev/tutorials/python_quickstart). To learn more about how you can use the embeddings, check out the [examples](../examples?keywords=embed) available. To learn how to create them from scratch, see TensorFlow's [Word Embeddings](https://www.tensorflow.org/text/guide/word_embeddings){:.external} tutorial."
]
}
],
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