Tutorials

We provide step-by-step guides to get you started. We cover the following use-cases:

=== card {: href=/tutorials/spacy101 }

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**Spacy representations**

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Learn the basics of how documents are represented with spaCy.

=== card {: href=/tutorials/matching-a-terminology }

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**Matching a terminology**

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Extract phrases that belong to a given terminology.

=== card {: href=/tutorials/qualifying-entities }

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**Qualifying entities**

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Ensure extracted concepts are not invalidated by linguistic modulation.

=== card {: href=/tutorials/detecting-dates }

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**Detecting dates**

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Detect and parse dates in a text.

=== card {: href=/tutorials/multiple-texts }

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**Processing multiple texts**

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Improve the inference speed of your pipeline

=== card {: href=/tutorials/reason }

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**Detecting hospitalisation reason**

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Identify spans mentioning the reason for hospitalisation or tag entities as the reason.

=== card {: href=/tutorials/endlines }

↵ **Detecting false endlines**

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Classify each line end and add the `excluded` attribute to these tokens.

=== card {: href=/tutorials/aggregating-results }

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**Aggregating results**

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Aggregate the results of your pipeline at the document level.

=== card {: href=/advanced-tutorials/fastapi }

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**FastAPI**

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Deploy your pipeline as an API.

=== card {: href=/tutorials/visualization }

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**Visualization**

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Quickly visualize the results of your pipeline as annotations or tables.

=== card {: href=/tutorials/make-a-training-script }

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**Deep learning tutorial**

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Learn how EDS-NLP handles training deep-neural networks.

=== card {: href=/tutorials/training }

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**Training API**

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Learn how to quicky train a deep-learning model with `edsnlp.train`.

=== card {: href=/tutorials/tuning }

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**Hyperparameter Tuning**

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Learn how to tune hyperparameters of a model with `edsnlp.tune`.