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Explosion in 2021: Our Year in Review

Explosion

We found an investor that fits our strategy, we released spaCy v3, the work on Prodigy Teams is in full swing, and the team has grown a lot. Jan 19: The new year started with the Portuguese translation of our free spaCy online course: PLN avançado com spaCy. So here’s our look back at our highlights of the year 2021.

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Implementing a custom trainable component for relation extraction

Explosion

In this blog post, we’ll go over the process of building a custom relation extraction component using spaCy and Thinc. In spaCy v3 , we introduced a new, flexible training configuration system that gives you much more control over the various components in your NLP pipeline. This requires three main steps.

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Emotion Classification with SpaCy v3 & Comet

Heartbeat

Photo by Nik on Unsplash If you are a natural language processing researcher or have an interest in this field, you have surely come across SpaCy or you are very close to it! SpaCy, a free, open source natural language processing library developed in Python, is very popular for use in real products. shuffle(seed=34).take(5000)

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Beyond Accuracy: Robustness Testing of Named Entity Recognition Models with LangTest

John Snow Labs

In this blog, we’ll dive into LangTest , a way to go beyond just accuracy and explore how well Named Entity Recognition models can handle the twists and turns of real language out there. Trained on the MIMIC-III dataset, it is compatible with spaCy v3+. Percocet 5/325 mg 2 tablets q.4 Neurontin 400 mg p.o.

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Healthsea: an end-to-end spaCy pipeline for exploring health supplement effects

Explosion

Read about the journey of developing Healthsea, an end-to-end spaCy pipeline for analyzing user reviews to supplementary products and extracting their potential effects on health. ? I’m a machine learning engineer at Explosion, and together with our fantastic team , we’ve been working on Healthsea to further expand the spaCy universe ?.

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Evaluating Robustness and Bias in Healthcare Named Entity Recognition Models

John Snow Labs

In this blog post, we will explore the evaluation of robustness and bias in healthcare Named Entity Recognition (NER) models. Trained on the MIMIC-III dataset, it is compatible with spaCy v3+. daily, Prevacid 30 mg daily, Avandia 4 mg daily, Norvasc 10 mg daily, Lexapro 20 mg daily, aspirin 81 mg daily, Senna 2 tablets p.o.

NLP 52
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Evaluating Robustness and Bias in Healthcare Named Entity Recognition Models

John Snow Labs

In this blog post, we will explore the evaluation of robustness and bias in healthcare Named Entity Recognition (NER) models. Trained on the MIMIC-III dataset, it is compatible with spaCy v3+. daily, Prevacid 30 mg daily, Avandia 4 mg daily, Norvasc 10 mg daily, Lexapro 20 mg daily, aspirin 81 mg daily, Senna 2 tablets p.o.

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